Runway
Runway is a lightweight wrapper around infrastructure deployment (e.g. CloudFormation, Terraform, Serverless) & linting (e.g. yamllint) tools to ease management of per-environment configs & deployment.
Installation
To enable Runway to conform to our users’ varying use cases, we have made it available via three different install methods - cURL, npm, and pip.
cURL
Arguably the easiest way to install Runway is by using curl. Use one of the endpoints below to download a single-binary executable version of Runway based on your operating system.
Operating System |
Endpoint |
|---|---|
Linux |
|
macOS |
|
Windows |
curl -L https://oni.ca/runway/latest/linux -o runway
curl -L https://oni.ca/runway/latest/osx -o runway
Invoke-WebRequest -Uri "https://oni.ca/runway/latest/windows" -OutFile runway
Note
To install a specific version of Runway, you can replace latest
with a version number.
Usage
To use the single-binary, run it directly as shown below. Please note that
after download, you may need to adjust the permissions before it can be
executed. (eg. Linux/macOS:chmod +x runway)
$ ./runway deploy
Suggested use: CloudFormation or Terraform projects
npm
Runway is published on npm as @onica/runway.
It currently contains binaries to support macOS, Ubuntu, and Windows.
While Runway can be installed globally like any other npm package, we strongly recommend using it per-project as a dev dependency. See Why Version Lock Per-Project for more info regarding this suggestion.
$ npm i -D @onica/runway
Usage
$ npx runway deploy
Suggested use: Serverless or AWS CDK projects
pip
Runway runs on Python 2.7 and Python 3.5+.
Runway is hosted on PyPI as the package named runway.
It can be installed like any other Python package, but we instead strongly recommend using it
per-project with poetry.
See Why Version Lock Per-Project for more info regarding this suggestion.
Suggested use: Python projects
poetry add runway
pip install --user runway
# or (depending on how Python was installed)
pip install runway
Usage
poetry run runway --help
runway --help
Why Version Lock Per-Project
Locking the version of Runway per-project will allow you to:
Specify the version(s) of Runway compatible with your deployments config
Ensure Runway executions are performed with the same version (regardless of where/when they occur – avoids the dreaded “works on my machine”)
Upgrades
Contents
During a Runway upgrade (especially coming from a 0.x version) you may required to make changes to your configuration or modules. This page will describe common issues when upgrading and how to resolve them.
Updating the Runway Config File
You may need to update your Runway config file structure depending on how old of a Runway version you are upgrading from. Some config keys have changed in spelling, may make use of _ instead of -, or have different functionality altogether. For example, compare this old config file:
deployments:
- modules:
- module-1.cfn
- module-2.cfn
- module-3.cfn
regions:
- us-east-1
account-id:
prod: 123412341234
assume-role:
post_deploy_env_revert: true
prod: arn:aws:iam::123412341234:role/my-deployment-role
environments:
prod:
namespace: my-account
environment: prod
To this newer version:
variables:
account_id:
prod: 123412341234
assume_role:
prod: arn:aws:iam::123412341234:role/my-deployment-role
parameters:
prod:
namespace: my-account
environment: prod
deployments:
- modules:
- module-1.cfn
- module-2.cfn
- module-3.cfn
regions:
- us-east-1
account_id: ${var account_id.${env DEPLOY_ENVIRONMENT}}
assume_role:
arn: ${var assume_role.${env DEPLOY_ENVIRONMENT}}
post_deploy_env_revert: true
environments:
prod: true
parameters: ${var parameters.${env DEPLOY_ENVIRONMENT}}
In the above example, we’ve taken advantage of Runway’s variables key and we dynamically reference it based on our DEPLOY_ENVIRONMENT. We also updated account-id and assume-role to account_id and assume_role.
Runway is very flexible about how you can structure your config, the above is only an example of one way to adjust it. Just keep in mind while upgrading that if you receive errors as soon as you start a runway command, it is likely due to a config file error or no longer supported directive.
Migration from Stacker to CFNgin
Older versions of Runway used Stacker, which was then forked and included into the Runway project as CFNgin. This causes a few concerns while migrating older deployments.
Update References to Stacker
See Migrating from Stacker for info on converting your older Stacker modules into CFNgin compatible versions.
Migration of Stacker Blueprints
In some environments, you may see usage of Stacker “Blueprints”. These are Python scripts leveraging Troposphere to generate CloudFormation templates programmatically. While these can be incredibly powerful, they also come with a Python experience dependency and are prone to breaking due to AWS or Runway changes. In older deployments if the blueprint contains references to stacker it will also need to be updated to use the new cfngin library after a Runway upgrade, as described in Migrating from Stacker.
In most cases it is easiest to:
Navigate to the AWS CloudFormation Console,
find the stack that was deployed using the blueprint,
copy its CloudFormation template data (optionally converting it to YAML on the way); and,
convert the deployment in Runway to use that static template so you can eliminate the blueprint.
This process leaves you with a much more simple to manage static template.
A Note on Tagging in Stacker Modules
stacker_namespace / cfngin_namespace tag
If a Stacker/CFNgin deployment doesn’t have a tags key defined, a default value is used:
Stacker:
stacker_namespace: ${namespace}
CFNgin:
cfngin_namespace: ${namespace}
Because of this if you are upgrading a Stacker module without the tags key defined, you’ll see Runway attempting to adjust the tags on every resource in the module. This is because it is updating the default stacker_namespace tag to a cfngin_namespace tag. If you’d like to prevent this behavior, you can add a tags key as follows:
tags:
stacker_namespace: ${namespace}
The above usage will cause CFNgin to keep the old stacker_namespace tag with its original value, eliminating the need for changes to tags on resources.
Int to String Errors
When defining a tags key directly onto a CFNgin stack definition (not the top level tags key in the CFNgin config file), you may see an error regarding using an int instead of a string. For instance:
# This may return a "must be of type string" error
my-stack-definition:
template_path: ./my-templates/my-cloudformation-template.yaml
tags:
CostCenter: 1234
This can be resolved by enclosing your numerical value in quotes:
# This may return a "must be of type string" error
my-stack-definition:
template_path: ./my-templates/my-cloudformation-template.yaml
tags:
CostCenter: "1234"
Updates to Lookups
Some lookup usage may have changed slightly. Here’s some examples:
# This generates a deprecation warning in newer Runway versions
VpcId: ${rxref vpc::VpcId}
# This is the new usage
VpcId: ${rxref vpc.VpcId}
# This generates an unknown lookup error
SlackUrl: ${ssmstore us-east-1@/devops/slack_hook}
# This is the new usage
SlackUrl: ${ssm /devops/slack_hook}
Getting Started Guide
Contents
Basic Concepts
Welcome to Runway! To get a basic understanding of Runway, we have listed out the key concepts below that you will need to get started with deploying your first module.
Runway Config File
The Runway config file is usually stored at the root of a project repo. It defines the modules that will be managed by Runway.
Deployment
A deployment contains a list of modules and options for all the modules in the deployment. A Runway config file can contain multiple deployments and a deployment can contain multiple modules.
Module
A module is a directory containing a single infrastructure as code tool configuration of an application, a component, or some infrastructure (eg. a set of CloudFormation templates). It is defined in a deployment by path. Modules can also contain granular options that only pertain to it.
Deploy Environment
Deploy environments are used for selecting the options/variables/parameters to
be used with each modules <module>.
They can be defined by the name of a directory (if its not a git repo),
git branch, or environment variable (DEPLOY_ENVIRONMENT).
Standard environments would be something like prod, dev, and test.
No matter how the environment is determined, the name is made available
to be consumed by your modules as the DEPLOY_ENVIRONMENT environment variable.
Deploying Your First Module
Create a directory for our project and change directory into the new directory.
$ mkdir sample-project && cd sample-project
Initialize the the new directory as a git repository and checkout branch ENV-dev. This will give us an environment of dev.
$ git init && git checkout -b ENV-dev
Download Runway using curl. Be sure to use the endpoint that corresponds to your operating system. Then, change the downloaded file’s permissions to allow execution.
$ curl -L https://oni.ca/runway/latest/linux -o runway $ chmod +x runway
$ curl -L https://oni.ca/runway/latest/osx -o runway $ chmod +x runway
Invoke-WebRequest -Uri "https://oni.ca/runway/latest/windows" -OutFile runway
Use Runway to generate a sample module using the gen-sample command. This will give us a preformatted module<runway-module that is ready to be deployed after we change a few variables. To read more about the directory structure, see Repo Structure.
$ ./runway gen-sample cfn
To finish configuring our CloudFormation module, lets open the
dev-us-east-1.envfile that was created insampleapp.cfn/. Here is where we will define values for our stacks that will be deployed as part of the dev environment in the us-east-1 region. Replace the place holder values in this file with your own information. It is important that thecfngin_bucket_namevalue is globally unique for this example as it will be used to create a new S3 bucket.dev-us-east-1.envnamespace: onica-dev customer: onica environment: dev region: us-east-1 # The CFNgin bucket is used for CFN template uploads to AWS cfngin_bucket_name: cfngin-onica-us-east-1
With the module ready to deploy, now we need to create our Runway config file. To do this, use the new command to generate a sample file at the root of the project repo.
$ ./runway new
runway.yml--- # See full syntax at https://docs.onica.com/projects/runway deployments: - modules: - nameofmyfirstmodulefolder - nameofmysecondmodulefolder # - etc... regions: - us-east-1
Now, we need to modify the
runway.ymlfile that was just created to tell it where the module is located that we want it to deploy and what regions it will be deployed to. Each module type has their own configuration options which are described in more detail in the Module Configurations section but, for this example we are only concerned with the CloudFormation module configuration.runway.yml--- # See full syntax at https://docs.onica.com/projects/runway deployments: - modules: - sampleapp.cfn regions: - us-east-1
Before we deploy, it is always a good idea to know how the module will impact the currently deployed infrastructure in your AWS account. This is less of a concern for net-new infrastructure as it is when making modifications. But, for this example, lets run the plan command to see what is about to happen.
$ ./runway plan
We are finally ready to deploy! Use the deploy command to deploy our module.
$ ./runway deploy
We have only scratched the surface with what is possible in this example. Proceed below to find out how to delete the module we just deployed or, review the pages linked throughout this section to learn more about what we have done to this point before continuing.
Deleting Your First Module
From the root of the project directory we created in Deploying Your First Module we only need to run the destroy command to remove what we have deployed.
$ ./runway destroy
Execution Without A TTY (non-interactive)
Runway allows you to set an environment variable to allow execution without a
TTY or if STDIN is closed.
This allows users to execute Runway deployments in
their CI/CD infrastructure as code deployment systems avoiding the
EOF when reading a line error message.
In order to execute runway without a TTY, set the CI environment variable
before your runway [deploy|destroy] execution.
Important
Executing Runway in this way will cause Runway to perform updates in your environment without prompt. Use with caution.
Quickstart Guides
CloudFormation Quickstart
Prepare the project directory. See Repo Structure for more details.
$ mkdir my-app && cd my-app $ git init && git checkout -b ENV-dev
Download/install Runway. To see available install methods, see Installation.
Use Runway to generate a sample CloudFormation module<runway-module, edit the values in the environment file, and create a Runway config file to use the module.
$ runway gen-sample cfn $ sed -i -e "s/CUSTOMERNAMEHERE/mydemo/g; s/ENVIRONMENTNAMEHERE/dev/g; s/cfngin-/cfngin-$(uuidgen|tr "[:upper:]" "[:lower:]")-/g" sampleapp.cfn/dev-us-east-1.env $ cat <<EOF >> runway.yml --- # Full syntax at https://github.com/onicagroup/runway deployments: - modules: - sampleapp.cfn regions: - us-east-1 EOF
$ runway gen-sample cfn $ (Get-Content sampleapp.cfn\dev-us-east-1.env).replace('CUSTOMERNAMEHERE', 'mydemo') | Set-Content sampleapp.cfn\dev-us-east-1.env $ (Get-Content sampleapp.cfn\dev-us-east-1.env).replace('ENVIRONMENTNAMEHERE', 'dev') | Set-Content sampleapp.cfn\dev-us-east-1.env $ (Get-Content sampleapp.cfn\dev-us-east-1.env).replace('cfngin-', 'cfngin-' + [guid]::NewGuid() + '-') | Set-Content sampleapp.cfn\dev-us-east-1.env $ $RunwayTemplate = @" --- # Full syntax at https://github.com/onicagroup/runway deployments: - modules: - sampleapp.cfn regions: - us-east-1 "@ $RunwayTemplate | Out-File -FilePath runway.yml -Encoding ASCII
Deploy the stack.
$ runway deploy
Now our stack is available at mydemo-dev-sampleapp, e.g.:
$ aws cloudformation describe-stack-resources --region us-east-1 --stack-name mydemo-dev-sampleapp
Conduit (Serverless & CloudFront) Quickstart
The Medium.com-clone “RealWorld” demo app named Conduit provides a simple demonstration of using Runway to deploy a Serverless Framework backend with an Angular frontend.
Contents
Prerequisites
An AWS account, and configured terminal environment for interacting with it with an admin role.
The following installed tools:
awscli
git (Available out of the box on macOS)
npm
python
yarn
Setup
Prepare the project directory. See Repo Structure for more details.
$ mkdir conduit $ cd conduit $ git init $ git checkout -b ENV-dev
Download/install Runway. To see available install methods, see Installation.
Download the source files.
$ curl -O https://codeload.github.com/anishkny/realworld-dynamodb-lambda/zip/v1.0.0 $ unzip v1.0.0 $ rm v1.0.0 $ mv realworld-dynamodb-lambda-1.0.0 backend && cd backend $ sed -i '/package-lock\.json/d' .gitignore $ echo '.dynamodb' >> .gitignore $ npm install $ cd .. $ curl -O https://codeload.github.com/gothinkster/angular-realworld-example-app/zip/35a66d144d8def340278cd55080d5c745714aca4 $ unzip 35a66d144d8def340278cd55080d5c745714aca4 $ rm 35a66d144d8def340278cd55080d5c745714aca4 $ mv angular-realworld-example-app-35a66d144d8def340278cd55080d5c745714aca4 frontend && cd frontend $ mkdir scripts $ cd scripts && { curl -O https://raw.githubusercontent.com/onicagroup/runway/master/quickstarts/conduit/build.js ; cd -; } $ sed -i 's/^\s*"build":\s.*$/ "build": "node scripts\/build",/' package.json $ sed -i 's/^\s*"rxjs":\s.*$/ "rxjs": "~6.3.3",/' package.json $ npm install $ curl -O https://raw.githubusercontent.com/onicagroup/runway/master/quickstarts/conduit/update_env_endpoint.py $ cd .. $ curl -O https://raw.githubusercontent.com/onicagroup/runway/master/quickstarts/conduit/runway.yml
$ [Net.ServicePointManager]::SecurityProtocol = [Net.SecurityProtocolType]::Tls12 $ Invoke-WebRequest "https://codeload.github.com/anishkny/realworld-dynamodb-lambda/zip/v1.0.0" -OutFile v1.0.0.zip $ Expand-Archive v1.0.0.zip . $ Remove-Item v1.0.0.zip -Force $ Rename-Item realworld-dynamodb-lambda-1.0.0 backend && cd backend $ (gc .\.gitignore -raw).Replace("package-lock.json`n", "") | sc .\.gitignore $ ".dynamodb`r`n" | Out-File .\.gitignore -Append -Encoding UTF8 $ (gc .\package.json) -replace "dynamodb install .*$", "dynamodb install`"" | Out-File .\package.json -Force -Encoding UTF8 $ npm install $ cd .. $ Invoke-WebRequest "https://codeload.github.com/gothinkster/angular-realworld-example-app/zip/35a66d144d8def340278cd55080d5c745714aca4" -OutFile 35a66d144d8def340278cd55080d5c745714aca4.zip $ Expand-Archive 35a66d144d8def340278cd55080d5c745714aca4.zip . $ Remove-Item 35a66d144d8def340278cd55080d5c745714aca4.zip -Force $ Rename-Item angular-realworld-example-app-35a66d144d8def340278cd55080d5c745714aca4 frontend && cd frontend $ (gc .\package.json -raw).Replace("`"rxjs`": `"^6.2.1`"", "`"rxjs`": `"~6.3.3`"") | sc .\package.json $ mkdir scripts $ Invoke-WebRequest "https://raw.githubusercontent.com/onicagroup/runway/master/quickstarts/conduit/build.js" -OutFile scripts/build.js $ (gc .\package.json) -replace "^\s*`"build`":\s.*$", " `"build`": `"node scripts/build`"," | Out-File .\package.json -Force -Encoding UTF8 $ npm install $ Invoke-WebRequest "https://raw.githubusercontent.com/onicagroup/runway/master/quickstarts/conduit/update_env_endpoint.py" -OutFile update_env_endpoint.py $ cd .. $ Invoke-WebRequest "https://raw.githubusercontent.com/onicagroup/runway/master/quickstarts/conduit/pyproject.toml" -OutFile pyproject.toml $ Invoke-WebRequest "https://raw.githubusercontent.com/onicagroup/runway/master/quickstarts/conduit/runway.yml" -OutFile runway.yml
Deploying
Execute runway deploy, enter all (to deploy the backend
followed by the frontend).
Deployment will take some time (mostly waiting for the CloudFront distribution
to stabilize).
The CloudFront domain at which the site can be reached will be displayed near the last lines of output once deployment is complete, e.g.:
staticsite: sync & CF invalidation of E17B5JWPMTX5Z8 (domain ddy1q4je03d7u.cloudfront.net) complete
Teardown
Execute runway destroy, enter all.
The backend DynamoDB tables will still be retained after the destroy is complete. They must be deleted separately.
for i in realworld-dev-articles realworld-dev-comments realworld-dev-users; do aws dynamodb delete-table --region us-east-1 --table-name $i; done
foreach($table in @("realworld-dev-articles", "realworld-dev-comments", "realworld-dev-users"))
{
CMD /C "aws dynamodb delete-table --region us-east-1 --table-name $table"
}
Next Steps / Additional Notes
The serverless-plugin-export-endpoints plugin
is a good alternative to the custom update_env_endpoint.py script used
above to update the environment file.
Permissions
The specific IAM permissions required to manage the resources in this demo are as follows
# CloudFormation
- cloudformation:CreateStack
- cloudformation:DeleteStack
- cloudformation:CreateChangeSet
- cloudformation:DescribeChangeSet
- cloudformation:DeleteChangeSet
- cloudformation:DescribeStackResource
- cloudformation:DescribeStackResources
- cloudformation:DescribeStacks
- cloudformation:DescribeStackEvents
- cloudformation:GetTemplate
- cloudformation:UpdateStack
- cloudformation:ExecuteChangeSet
- cloudformation:ValidateTemplate
# Serverless
- apigateway:GET
- apigateway:DELETE
- apigateway:POST
- apigateway:PUT
- lambda:AddPermission
- lambda:CreateAlias
- lambda:CreateFunction
- lambda:DeleteAlias
- lambda:DeleteFunction
- lambda:GetFunction
- lambda:GetFunctionConfiguration
- lambda:ListVersionsByFunction
- lambda:PublishVersion
- lambda:UpdateAlias
- lambda:UpdateFunctionCode
- lambda:UpdateFunctionConfiguration
- iam:CreateRole
- iam:DeleteRole
- iam:DeleteRolePolicy
- iam:GetRole
- iam:PassRole
- iam:PutRolePolicy
- logs:CreateLogGroup
- logs:DeleteLogGroup
- logs:DescribeLogGroups
- s3:CreateBucket
- s3:DeleteBucket
- s3:DeleteBucketPolicy
- s3:DeleteObject
- s3:DeleteObjectVersion
- s3:GetObjectVersion
- s3:ListBucket
- s3:ListBucketVersions
- s3:PutBucketVersioning
- s3:PutBucketPolicy
- s3:PutLifecycleConfiguration
# Frontend
- cloudfront:CreateCloudFrontOriginAccessIdentity
- cloudfront:CreateDistribution
- cloudfront:CreateInvalidation
- cloudfront:DeleteCloudFrontOriginAccessIdentity
- cloudfront:DeleteDistribution
- cloudfront:GetCloudFrontOriginAccessIdentity
- cloudfront:GetCloudFrontOriginAccessIdentityConfig
- cloudfront:GetDistribution
- cloudfront:GetDistributionConfig
- cloudfront:GetInvalidation
- cloudfront:ListDistributions
- cloudfront:TagResource
- cloudfront:UntagResource
- cloudfront:UpdateCloudFrontOriginAccessIdentity
- cloudfront:UpdateDistribution
- s3:DeleteBucketWebsite
- s3:GetBucketAcl
- s3:GetObject
- s3:PutBucketAcl
- s3:GetBucketWebsite
- s3:PutBucketWebsite
- s3:PutObject
- ssm:GetParameter
- ssm:PutParameter
# Backend
- dynamodb:CreateTable
- dynamodb:DeleteTable
- dynamodb:DescribeTable
- dynamodb:TagResource
- dynamodb:UntagResource
- dynamodb:UpdateTable
Other Ways to Use Runway
While we recommend using one of the install methods outlined in the Installation section, we realize that these may not be an option for some so we have provided a CloudFormation template for spinning up a deploy environment in AWS and a Docker image/Dockerfile that can be used to run Runway.
Contents
CloudFormation
This CloudFormation template is probably the easiest and quickest way to go from “zero to Runway” as it allows for using an IAM Role eliminate the need to configure API keys. The template will deploy your preference of Linux or Windows Runway host. Windows Runway host includes Visual Studio Code, which some users may find easier for manipulating Runway config files.
Docker
Docker users can build their own Docker image to run a local Runway container or modify this Dockerfile to build a Runway image to suit specific needs.
Private Static Site (Auth@Edge) Quickstart
The Runway built-in sample generation of a basic React app will be used as a simple demonstration of creating an authentication backed single page application.
Contents
Prerequisites
An AWS account, and configured terminal environment for interacting with it with an admin role.
The following installed tools:
git (Available out of the box on macOS)
npm
Setup
Project Setup
Download/install Runway. To see available install methods, see Installation.
From a directory of your choosing run the following to generate a sample React project:
$ runway gen-sample static-react
A new folder will be created entitled
static-react. If you’d like your project to have a different name feel free to change it at this time.$ mv static-react my-static-site
Change directories into the new project folder and prepare the project directory. See Repo Structure for more details.
$ cd my-static-site $ git init && git checkout -b ENV-dev
User Pool Setup
The default
runway.ymldocument that is provided withgen-sample static-reactis a good baseline document for deploying a standard static single page application without the need of authentication. In this example we’ll be leveragingAuth@Edgeto provide protection to our application, not allowing anyone to view or download site resources without first authenticating. To accomplish this we need to create a Cognito UserPool. Login to your AWS Console and search for cognito.
Click
Manage User Pools
Click
Create a user pool
You will be asked to provide a name for your User Pool. For our example we will be using a default Cognito User Pool, but you can
Step through settingsto customize your pool if you so choose. After entering your Pool name click theReview defaultsbutton.
Review all the settings are accurate prior to clicking
Create pool.
Next let’s create a test user to verify our authentication functionality after deployment. Click the
Users and groupslist link.
Click
Create user
In the form provided give a valid email address for the
Username (Required)andEmailentries. EnsureSend an invitation to this new user?is checked so you can receive the temporary password to access the site. Click theCreate userbutton.
Check the email address provided, you should receive a notification email from Cognito with the username and password that will need to be used for initial authentication.
Now we need to retrieve the ARN for the User Pool we just created and add it to the
deployments -> modules -> environments -> devsection of ourrunway.ymldocument. Click theGeneral Settingslist link to retrieve the ARN.
staticsite_user_pool_arn: YOUR_USER_POOL_ARN
Domain Aliases with ACM Certificate
In this example we are going to be using an alias custom domain name to identify the CloudFront Distribution. This series of steps is optional, a domain will still be provided with the Distribution if you choose not to use a custom domain. This guide assumes that you have already purchased and registered a custom domain and created and validated an ACM certificate.
The ARN of the ACM certificate is required when providing an alias domain name. From the search bar of the AWS console locate
certificate manager. In this screen dropdown the details of your issued and validated certificate and locate the ARN.
Create two entries in the
runway.ymlconfiguration file under thedeployments -> modules -> environments -> devheading. One for the alias we’re looking to provide, and the other for it’s ARN.staticsite_aliases: YOUR_CUSTOM_DOMAIN_NAMES_COMMA_SEPARATED staticsite_acmcert_arn: YOUR_ACM_ARN
Cleanup
By default the gen-sample static-react sample runway.yaml document comes with staticsite_cf_disable: true added.
Due to the nature of the authorization a Distribution is required.
Remove this line from your config file.
Deploying
Execute runway deploy.
Deployment will take some time (mostly waiting for the CloudFront distribution to stabilize).
The CloudFront domain at which the site can be reached will be displayed near the last lines of output once deployment is complete, e.g.:
staticsite: sync & CF invalidation of E17B5JWPMTX5Z8 (domain ddy1q4je03d7u.cloudfront.net) complete
Since we’re using a custom domain alias the Distribution will also be accessible by that domain.
Accessing and Authorizing
Authorizing
From your browser enter either the CloudFront Distribution domain or the alias you provided. You will be greeted with the Cognito login screen. Enter the username and temporary password you received in step 9 of User Pool Setup:
You will be asked to change your password based on the validation requirements you specified when creating the User Pool. Once you have satisfied the requirements click
Send
You will be greeted with the default React App home page:
Sign-Out
By default a /sign-out path is provided to sign out of Cognito.
Teardown
Execute runway destroy.
Commands
$ runway --help
Usage: runway [OPTIONS] COMMAND [ARGS]...
Runway CLI.
Full documentation available at https://docs.onica.com/projects/runway/
Options:
--version Show the version and exit.
--debug Supply once to display Runway debug logs. Supply twice to
display all debug logs.
--no-color Disable color in Runway's logs.
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
...
deploy
$ runway deploy --help
Usage: runway deploy [OPTIONS]
Deploy infrastructure as code.
Process
-------
1. Determines the deploy environment.
- "-e, --deploy-environment" option
- "DEPLOY_ENVIRONMENT" environment variable
- git branch name
- strips "ENV-" prefix, master is converted to common
- ignored if "ignore_git_branch: true"
- name of the current working directory
2. Selects deployments & modules to deploy.
- (default) prompts
- (tags) module contains all tags
- (non-interactive) all
3. Deploys selected deployments/modules in the order defined.
Options:
--ci Run in non-interactive mode.
--debug Supply once to display Runway debug logs.
Supply twice to display all debug logs.
-e, --deploy-environment <env-name>
Manually specify the name of the deploy
environment.
--no-color Disable color in Runway's logs.
--tag <tag>... Select modules by tag or tags. This option
can be specified more than once to build a
list of tags that are treated as "AND".
(e.g. "--tag <tag1> --tag <tag2>" would
select all modules with BOTH tags).
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway deploy
$ runway deploy --ci --deploy-environment example
$ runway deploy --tag tag1 --tag tag2
destroy
$ runway destroy --help
Usage: runway destroy [OPTIONS]
Destroy infrastructure as code.
Process
-------
1. Determines the deploy environment.
- "-e, --deploy-environment" option
- "DEPLOY_ENVIRONMENT" environment variable
- git branch name
- strips "ENV-" prefix, master is converted to common
- ignored if "ignore_git_branch: true"
- name of the current working directory
2. Selects deployments & modules to deploy.
- (default) prompts
- (tags) module contains all tags
- (non-interactive) all
3. Destroys selected deployments/modules in reverse the order defined.
Options:
--ci Run in non-interactive mode.
--debug Supply once to display Runway debug logs.
Supply twice to display all debug logs.
-e, --deploy-environment <env-name>
Manually specify the name of the deploy
environment.
--no-color Disable color in Runway's logs.
--tag <tag>... Select modules by tag or tags. This option
can be specified more than once to build a
list of tags that are treated as "AND".
(e.g. "--tag <tag1> --tag <tag2>" would
select all modules with BOTH tags).
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway destroy
$ runway destroy --ci --deploy-environment example
$ runway destroy --tag tag1 --tag tag2
dismantle
$ runway dismantle --help
Usage: runway dismantle [OPTIONS]
Alias of "runway destroy".
For more information, refer to the output of "runway destroy --help".
Options:
--ci Run in non-interactive mode.
--debug Supply once to display Runway debug logs.
Supply twice to display all debug logs.
-e, --deploy-environment <env-name>
Manually specify the name of the deploy
environment.
--no-color Disable color in Runway's logs.
--tag <tag>... Select modules by tag or tags. This option
can be specified more than once to build a
list of tags that are treated as "AND".
(e.g. "--tag <tag1> --tag <tag2>" would
select all modules with BOTH tags).
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway dismantle
$ runway dismantle --ci --deploy-environment example
$ runway dismantle --tag tag1 --tag tag2
docs
$ runway docs --help
Usage: runway docs [OPTIONS]
Open the Runway documentation web site using the default web browser.
Options:
--debug Supply once to display Runway debug logs. Supply twice to
display all debug logs.
--no-color Disable color in Runway's logs.
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway docs
envvars
$ runway envvars --help
Usage: runway envvars [OPTIONS]
Output "env_vars" defined in the Runway config file.
OS environment variables can be set in the Runway config file for different
Runway environments (e.g. dev & prod KUBECONFIG values). This command allows
access to these values for use outside of Runway.
NOTE: Only outputs "env_vars" defined in deployments, not modules.
Options:
--debug Supply once to display Runway debug logs.
Supply twice to display all debug logs.
-e, --deploy-environment <env-name>
Manually specify the name of the deploy
environment.
--no-color Disable color in Runway's logs.
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway envvars
$ eval "$(runway envvars)"
$ runway envvars --deploy-environment example
gen-sample
$ runway gen-sample --help
Usage: runway gen-sample [OPTIONS] COMMAND [ARGS]...
Generate a sample Runway module module/project.
The sample is created in the current directory. If a directory already
exists with the name Runway tries to use, the sample will not be created.
Options:
--debug Supply once to display Runway debug logs. Supply twice to
display all debug logs.
--no-color Disable color in Runway's logs.
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Commands:
cdk-csharp cdk + c# (sampleapp.cdk)
cdk-py cdk + py (sampleapp.cdk)
cdk-tsc cdk + tsc (sampleapp.cdk)
cfn cfngin + cfn (sampleapp.cfn)
cfngin cfngin + troposphere (sampleapp.cfn)
k8s-cfn-repo k8s + cfn (k8s-cfn-infrastructure)
k8s-flux-repo k8s + flux + tf (k8s-tf-infrastructure)
k8s-tf-repo k8s + tf (k8s-tf-infrastructure)
sls-py sls + python (sampleapp.sls)
sls-tsc sls + tsc (sampleapp.sls)
static-angular angular static site (static-angular)
static-react react static site (static-react)
tf tf (sampleapp.tf)
Example
$ runway gen-sample cfngin
$ runway gen-sample static-react
init
$ runway init --help
Usage: runway init [OPTIONS]
Run initialization/bootstrap steps.
Process
-------
1. Determines the deploy environment.
- "-e, --deploy-environment" option
- "DEPLOY_ENVIRONMENT" environment variable
- git branch name
- strips "ENV-" prefix, master is converted to common
- ignored if "ignore_git_branch: true"
- name of the current working directory
2. Selects deployments & modules to deploy.
- (default) prompts
- (tags) module contains all tags
- (non-interactive) all
3. Initializes/bootstraps selected deployments/modules in the order defined.
(e.g. "cdk bootstrap", "terraform init")
Steps By Module Type
--------------------
- AWS CDK: Runs "cdk bootstrap".
- CFNgin: Creates the "cfngin_bucket" if needed.
- Terraform: Runs "terraform init", changes the workspace if needed, runs
"terraform init" again if the workspace was changed, and finally
downloads/updates Terraform modules.
Options:
--ci Run in non-interactive mode.
--debug Supply once to display Runway debug logs.
Supply twice to display all debug logs.
-e, --deploy-environment <env-name>
Manually specify the name of the deploy
environment.
--no-color Disable color in Runway's logs.
--tag <tag>... Select modules by tag or tags. This option
can be specified more than once to build a
list of tags that are treated as "AND".
(e.g. "--tag <tag1> --tag <tag2>" would
select all modules with BOTH tags).
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway init
$ runway init --ci --deploy-environment example
$ runway init --tag tag1 --tag tag2
kbenv install
$ runway kbenv install --help
Usage: runway kbenv install [OPTIONS] [<version>]
Install the specified <version> of kubectl (e.g. v1.14.0).
If no version is specified, Runway will attempt to find and read a
".kubectl-version" file in the current directory. If this file doesn't
exist, nothing will be installed.
Compatible with https://github.com/alexppg/kbenv.
Options:
--debug Supply once to display Runway debug logs. Supply twice to
display all debug logs.
--no-color Disable color in Runway's logs.
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway kbenv install
$ runway kbenv install v1.14.0
kbenv list
$ runway kbenv list --help
Usage: runway kbenv list [OPTIONS]
List the versions of kubectl that have been installed by Runway and/or
kbenv.
Options:
--debug Supply once to display Runway debug logs. Supply twice to
display all debug logs.
--no-color Disable color in Runway's logs.
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway kbenv list
kbenv run
$ runway kbenv run --help
Usage: runway kbenv run [OPTIONS] <args>
Run a kubectl command.
Uses the version of kubectl specified in the ".kubectl-version" file in the
current directory.
IMPORTANT: When using options shared with Runway "--" must be placed before
the kubectl command.
Options:
--debug Supply once to display Runway debug logs. Supply twice to
display all debug logs.
--no-color Disable color in Runway's logs.
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway kbenv run version --client
$ runway kbenv run -- --help
kbenv uninstall
$ runway kbenv uninstall --help
Usage: runway kbenv uninstall [OPTIONS] [<version>]
Uninstall the specified <version> of kubectl (e.g. v1.14.0) or all installed
versions.
If no version is specified, Runway will attempt to find and read a
".kubectl-version" file in the current directory.
Options:
--all Uninstall all versions of kubectl.
--debug Supply once to display Runway debug logs. Supply twice to
display all debug logs.
--no-color Disable color in Runway's logs.
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway kbenv uninstall v1.21.0
$ runway kbenv uninstall --all
new
$ runway new --help
Usage: runway new [OPTIONS]
Create an example runway.yml file in the correct directory.
Options:
--debug Supply once to display Runway debug logs. Supply twice to
display all debug logs.
--no-color Disable color in Runway's logs.
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway new
$ runway new --debug
plan
Note
Currently only supported for AWS Cloud Development Kit (CDK), CloudFormation & Troposphere, and Terraform.
$ runway new --help
Usage: runway new [OPTIONS]
Create an example runway.yml file in the correct directory.
Options:
--debug Supply once to display Runway debug logs. Supply twice to
display all debug logs.
--no-color Disable color in Runway's logs.
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway plan
$ runway plan --ci --deploy-environment example
$ runway plan --tag tag1 --tag tag2
preflight
$ runway preflight --help
Usage: runway preflight [OPTIONS]
Alias of "runway test".
For more information, refer to the output of "runway test --help".
Options:
--debug Supply once to display Runway debug logs.
Supply twice to display all debug logs.
-e, --deploy-environment <env-name>
Manually specify the name of the deploy
environment.
--no-color Disable color in Runway's logs.
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway preflight
run-python
$ runway run-python --help
Usage: runway run-python [OPTIONS] <filename>
Execute a python script using a bundled copy of python.
This command can execute actions using python without requiring python to be
installed on a system. This is only applicable when installing a binary
release of Runway (not installed from PyPi). When installed from PyPI, the
current interpreter is used.
Options:
--debug Supply once to display Runway debug logs. Supply twice to
display all debug logs.
--no-color Disable color in Runway's logs.
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway run-python my_script.py
schema cfngin
$ runway schema cfngin --help
Usage: runway schema cfngin [OPTIONS]
Output JSON schema for CFNgin configuration files.
The schema that is output can be used to validate configuration files. It
can also be added to text editors to provide autocompletion, tool tips, and
suggestions within configuration files.
Options:
--debug Supply once to display Runway debug logs. Supply
twice to display all debug logs.
--indent <int> Number of spaces to use per indentation level when
output JSON. [default: 4]
--no-color Disable color in Runway's logs.
-o, --output <file-name> If provided, schema will be saved to a file
instead of being output to stdout.
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway schema cfngin --output cfngin-schema.json
schema runway
$ runway schema runway --help
Usage: runway schema runway [OPTIONS]
Output JSON schema Runway configuration files.
The schema that is output can be used to validate configuration files. It
can also be added to text editors to provide autocompletion, tool tips, and
suggestions within configuration files.
Options:
--debug Supply once to display Runway debug logs. Supply
twice to display all debug logs.
--indent <int> Number of spaces to use per indentation level when
output JSON. [default: 4]
--no-color Disable color in Runway's logs.
-o, --output <file-name> If provided, schema will be saved to a file
instead of being output to stdout.
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway schema runway --output runway-schema.json
takeoff
$ runway takeoff --help
Usage: runway takeoff [OPTIONS]
Alias of "runway deploy".
For more information, refer to the output of "runway deploy --help".
Options:
--ci Run in non-interactive mode.
--debug Supply once to display Runway debug logs.
Supply twice to display all debug logs.
-e, --deploy-environment <env-name>
Manually specify the name of the deploy
environment.
--no-color Disable color in Runway's logs.
--tag <tag>... Select modules by tag or tags. This option
can be specified more than once to build a
list of tags that are treated as "AND".
(e.g. "--tag <tag1> --tag <tag2>" would
select all modules with BOTH tags).
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway takeoff
$ runway takeoff --ci --deploy-environment example
$ runway takeoff --tag tag1 --tag tag2
taxi
$ runway taxi --help
Usage: runway taxi [OPTIONS]
Alias of "runway plan".
For more information, refer to the output of "runway plan --help".
Options:
--ci Run in non-interactive mode.
--debug Supply once to display Runway debug logs.
Supply twice to display all debug logs.
-e, --deploy-environment <env-name>
Manually specify the name of the deploy
environment.
--no-color Disable color in Runway's logs.
--tag <tag>... Select modules by tag or tags. This option
can be specified more than once to build a
list of tags that are treated as "AND".
(e.g. "--tag <tag1> --tag <tag2>" would
select all modules with BOTH tags).
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway taxi
$ runway taxi --ci --deploy-environment example
$ runway taxi --tag tag1 --tag tag2
test
$ runway test --help
Usage: runway test [OPTIONS]
Execute tests as defined in the Runway config file.
If one of the tests fail, the command will exit immediately unless
"required: false" is set on the failing test.
If the failing test is not required, the next test will be executed.
If any of the tests fail, the command will exit with a non-zero exit code.
Options:
--debug Supply once to display Runway debug logs.
Supply twice to display all debug logs.
-e, --deploy-environment <env-name>
Manually specify the name of the deploy
environment.
--no-color Disable color in Runway's logs.
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway test
tfenv install
$ runway tfenv install --help
Usage: runway tfenv install [OPTIONS] [<version>]
Install the specified <version> of Terraform (e.g. 0.12.0).
If no version is specified, Runway will attempt to find and read a
".terraform-version" file in the current directory. If this file doesn't
exist, nothing will be installed.
Options:
--debug Supply once to display Runway debug logs. Supply twice to
display all debug logs.
--no-color Disable color in Runway's logs.
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway tfenv install 0.12.0
tfenv list
$ runway tfenv list --help
Usage: runway tfenv list [OPTIONS]
List the versions of Terraform that have been installed by Runway and/or
tfenv.
Options:
--debug Supply once to display Runway debug logs. Supply twice to
display all debug logs.
--no-color Disable color in Runway's logs.
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway tfenv list
tfenv run
$ runway tfenv run --help
Usage: runway tfenv run [OPTIONS] <args>
Run a Terraform command.
Uses the version of Terraform specified in the ".terraform-version" file in
the current directory.
IMPORTANT: When using options shared with Runway "--" must be placed before
the Terraform command.
Options:
--debug Supply once to display Runway debug logs. Supply twice to
display all debug logs.
--no-color Disable color in Runway's logs.
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway tfenv run --version
$ runway tfenv run -- --help
tfenv uninstall
$ runway tfenv uninstall --help
Usage: runway tfenv uninstall [OPTIONS] [<version>]
Uninstall the specified <version> of Terraform (e.g. 0.12.0) or all
installed versions.
If no version is specified, Runway will attempt to find and read a
".terraform-version" file in the current directory.
Options:
--all Uninstall all versions of Terraform.
--debug Supply once to display Runway debug logs. Supply twice to
display all debug logs.
--no-color Disable color in Runway's logs.
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway tfenv uninstall 1.0.0
$ runway tfenv uninstall --all
whichenv
$ runway whichenv --help
Usage: runway whichenv [OPTIONS]
Print the current deploy environment name to stdout.
When run, the deploy environment will be determined from one of the
following (in order of precedence):
- "DEPLOY_ENVIRONMENT" environment variable
- git branch name (strips "ENV-" prefix, master => common)
- current working directory
Options:
--debug Supply once to display Runway debug logs. Supply twice to
display all debug logs.
--no-color Disable color in Runway's logs.
--verbose Display Runway verbose logs.
-h, --help Show this message and exit.
Example
$ runway whichenv
Runway Config File
The Runway config file is where all options are defined. It contains definitions for deployments, tests, and some global options that impact core functionality.
The Runway config file can have two possible names, runway.yml or runway.yaml.
It must be stored at the root of the directory containing the modules to be deployed.
Top-Level Configuration
- deployments: List[deployment]
A list of deployments that will be processed in the order they are defined. See Deployment for detailed information about defining this value.
Example
deployments: - name: example modules: - sampleapp-01.cfn - path: sampleapp-02.cfn regions: - us-east-1
- ignore_git_branch: bool = false
Optionally exclude the git branch name when determining the current deploy environment.
This can be useful when using the directory name or environment variable to set the deploy environment to ensure the correct value is used.
Example
ignore_git_branch: true
Note
The existence of
DEPLOY_ENVIRONMENTin the environment will automatically ignore the git branch.
- runway_version: str = ">=1.10.0"
Define the versions of Runway that can be used with this configuration file.
The value should be a PEP 440 compliant version specifier set.
Example
greater than or equal to 1.14.0runway_version: ">=1.14.0"
explicit versionrunway_version: "==14.0.0"
greater than or equal to 1.14.0 but less than 2.0.0runway_version: ">=1.14.0,<2.0.0" # or ~=1.14.0
New in version 1.11.0.
- tests: Optional[List[test]] = []
List of Runway test definitions that are executed with the test command command. See Test for detailed information about defining this value.
Example
tests: - name: Hello World type: script args: commands: - echo "Hello World"
- variables: Optional[Dict[str, Any]] = {}
Runway variables are used to fill values that could change based on any number of circumstances. They can also be used to simplify the Runway config file by pulling lengthy definitions into another YAML file. Variables can be consumed in the config file by using the var lookup in any field that supports Lookups.
By default, Runway will look for and load a
runway.variables.ymlorrunway.variables.yamlfile that is in the same directory as the Runway config file. The file path and name of the file can optionally be defined in the config file. If the file path is explicitly provided and the file can’t be found, an error will be raised.Variables can also be defined in the Runway config file directly. This can either be in place of a dedicated variables file, extend an existing file, or override values from the file.
Important
The
variablesand the variables file cannot contain lookups. If there is a lookup string in either of these locations, they will not be resolved.Example
deployments: - modules: - path: sampleapp.cfn env_vars: ${var env_vars} # exists in example-file.yml parameters: namespace: ${var namespace}-${env DEPLOY_ENVIRONMENT} regions: ${var regions.${env DEPLOY_ENVIRONMENT}} variables: file_path: example-file.yml namespace: example regions: dev: - us-east-1 - us-west-2
- variables.file_path: Optional[str]
Explicit path to a variables file that will be loaded and merged with the variables defined here.
Example
variables: file_path: some-file.yml
- variables.sys_path: Optional[str] = ./
Directory to use as the root of a relative
variables.file_path. If not provided, the current working directory is used.Example
variables: sys_path: ./../variables
Deployment
- class deployment
A deployment defines modules and options that affect the modules.
Deployments are processed during a deploy/destroy/plan action. If the processing of one deployment fails, the action will end.
During a deploy/destroy action, the user has the option to select which deployment will run unless the
CIenvironment variable (--cicli option) is set, the--tag <tag>...cli option was provided, or only one deployment is defined.Lookup Support
Important
Due to how a deployment is processed, some values are resolved twice. Once before processing and once during processing.
Because of this, the fields that are resolved before processing begins will not have access to values set during processing like
AWS_REGION,AWS_DEFAULT_REGION, andDEPLOY_ENVIRONMENTfor the pre-processing resolution which can result in aFailedLookuperror. To avoid errors during the first resolution due to the value not existing, provide a default value for the Lookup.The values mentioned will be set before the second resolution when processing begins. This ensures that the correct values are passed to the module.
Impacted fields are marked with an asterisk (*).
The following fields support lookups:
- account_alias: Optional[str] = None
An AWS account alias use to verify the currently assumed role or credentials. Verification is performed by listing the account’s alias and comparing the result to what is defined. This requires the credentials being used to have
iam:ListAccountAliasespermissions.Example
using a literal valuedeployments: - account_alias: example-dev
using a lookupdeployments: - account_alias: example-${env DEPLOY_ENVIRONMENT} - account_alias: ${var account_alias.${env DEPLOY_ENVIRONMENT}} variables: account_alias: dev: example-dev
Changed in version 2.0.0: No longer accepts a
typing.Dict.
- account_id: Optional[str] = None
An AWS account ID use to verify the currently assumed role or credentials. Verification is performed by getting the caller identity. This does not required any added permissions as it is allowed by default. However, it does require that
sts:GetCallerIdentityis not explicitly denied.Example
using a literal valuedeployments: - account_id: 123456789012
using a lookupdeployments: - account_id: ${var account_id.${env DEPLOY_ENVIRONMENT}} variables: account_id: dev: 123456789012
Changed in version 2.0.0: No longer accepts a
typing.Dict.
- assume_role: Optional[assume_role_definition, str] = {}
Assume an AWS IAM role when processing the deployment. The credentials being used prior to assuming the role must to
iam:AssumeRolepermissions for the role provided.Example
using a literal valuedeployments: - assume_role: arn:aws:iam::123456789012:role/name
using a lookup in a detailed definitiondeployments: - assume_role: arn: ${var assume_role.${env DEPLOY_ENVIRONMENT}} post_deploy_env_revert: True variables: assume_role: dev: arn:aws:iam::123456789012:role/name
Changed in version 2.0.0: No longer accepts a
typing.Dictdefining a value per deploy environment.
- env_vars: Optional[Dict[str, Union[List[str], str]]] = {}
Additional variables to add to the environment when processing the deployment.
Anything defined here is merged with the value of
module.env_vars.Example
using a lookup as the valuedeployments: - env_vars: NAME: value KUBECONFIG: - .kube - ${env DEPLOY_ENVIRONMENT} - config
using a lookup in the valuedeployments: - env_vars: ${var env_vars.${env DEPLOY_ENVIRONMENT}} variables: env_vars: dev: NAME: value
Changed in version 2.0.0: No longer accepts a
typing.Dictdefining a value per deploy environment. The entire value of the field is used for all environments.
- environments: Optional[Dict[str, Union[bool, List[str], str]]] = {}
Explicitly enable/disable the deployment for a specific deploy environment, AWS Account ID, and AWS Region combination. Can also be set as a static boolean value.
Anything defined here is merged with the value of
module.environments.Example
deployments: - environments: dev: True test: 123456789012 qa: us-east-1 prod: - 123456789012/ca-central-1 - us-west-2 - 234567890123
using a lookup as the valuedeployments: - environments: ${var environments} variables: environments: dev: True
Changed in version 1.4.0: Now acts as an explicit toggle for deploying modules to a set AWS Account/AWS Region. For passing values to a module,
deployment.parameters/module.parametersshould be used instead.Changed in version 2.0.0: If defined and the current deploy environment is missing from the definition, processing will be skipped.
- modules: List[Union[module, str]]
A list of modules to process as part of a deployment.
Example
deployments: - modules: - sampleapp-01.cfn - path: sampleapp-02.cfn
- module_options: Optional[Union[Dict[str, Any], str]] = {}
Options that are passed directly to the modules within this deployment.
Anything defined here is merged with the value of
module.options.Example
deployments: - module_options: example: value
using a lookup as the valuedeployments: - module_options: example: ${var example} variables: example: value
using a lookup in the valuedeployments: - module_options: ${var parameters} variables: parameters: example: value
- name: Optional[str] = None
The name of the deployment to be displayed in logs and the interactive selection menu.
Example
deployments: - name: networking
- parallel_regions: Optional[Union[List[str], str]] = []
A list of AWS Regions to process asynchronously.
Only one of
parallel_regionsorregionscan be defined.Asynchronous deployment only takes effect when running non-interactively. Otherwise processing will occur synchronously.
assume_role.post_deploy_env_revertwill always betruewhen run in parallel.Can be used in tandem with
module.parallel.Example
using a lookup as the valuedeployments: - parallel_regions: - us-east-1 - us-west-2 - ${var third_region.${env DEPLOY_ENVIRONMENT}} variables: third_region: dev: ca-central-1
using a lookup in the valuedeployments: - parallel_regions: ${var regions.${env DEPLOY_ENVIRONMENT}} variables: regions: - us-east-1 - us-west-2
New in version 1.3.0.
- parameters: Optional[Union[Dict[str, Any], str]] = {}
Used to pass variable values to modules in place of an environment configuration file.
Anything defined here is merged with the value of
module.parameters.Example
using a lookup as the valuedeployments: - parameters: namespace: example-${env DEPLOY_ENVIRONMENT}
using a lookup in the valuedeployments: - parameters: ${var parameters.${env DEPLOY_ENVIRONMENT}} variables: parameters: dev: namespace: example-dev
New in version 1.4.0.
- regions: Optional[Union[Dict[str, Union[List[str], str], List[str], str]] = []
A list of AWS Regions to process this deployment in.
Only one of
parallel_regionsorregionscan be defined.Can be used to define asynchronous processing similar to
parallel_regions.Example
synchronousdeployments: - regions: - us-east-1 - us-west-2
asynchronousdeployments: - regions: parallel: - us-east-1 - us-west-2 - ${var third_region.${env DEPLOY_ENVIRONMENT}} variables: third_region: dev: ca-central-1
using a lookup in the valuedeployments: - regions: ${var regions.${env DEPLOY_ENVIRONMENT}} variables: regions: - us-east-1 - us-west-2
Module
- class module
A module defines the directory to be processed and applicable options.
It can consist of CloudFormation, Terraform, Serverless Framework, AWS CDK, Kubernetes, or a Static Site. It is recommended to place the appropriate extension on each directory for identification (but it is not required). See Repo Structure for examples of a module directory structure.
Suffix/Extension
IaC Tool/Framework
.cdk.cfn.k8s.sls.tf.webA module is only deployed if there is a corresponding environment file present, it is explicitly enabled via
deployment.environments/module.environments, ordeployment.parameters/module.parametersis defined. The naming format of an environment file varies per module type. See Module Configurations for acceptable environment file name formats.Modules can be defined as a string or a mapping. The minimum requirement for a module is a string that is equal to the name of the module directory. Providing a string is the same as providing a value for
pathin a mapping definition.Using a mapping to define a module provides the ability to specify all the fields listed here.
Lookup Support
The following fields support lookups:
- class_path: Optional[str] = null
Note
Most users will never need to use this. It is only used for custom module type handlers.
Import path to a custom Runway module handler class. See Module Configurations for detailed usage.
Example
deployments: - modules: - class_path: runway.module.cloudformation.CloudFormation
- env_vars: Optional[Dict[str, Union[List[str], str]]] = {}
Additional variables to add to the environment when processing the deployment.
Anything defined here is merged with the value of
deployment.env_vars. Values defined here take precedence.Example
using a lookup as the valuedeployments: - modules: - env_vars: NAME: VALUE KUBECONFIG: - .kube - ${env DEPLOY_ENVIRONMENT} - config
using a lookup in the valuedeployments: - modules: - env_vars: ${var env_vars.${env DEPLOY_ENVIRONMENT}} variables: env_vars: dev: NAME: value
Changed in version 2.0.0: No longer accepts a
typing.Dictdefining a value per deploy environment. The entire value of the field is used for all environments.
- environments: Optional[Dict[str, Union[bool, List[str], str]]] = {}
Explicitly enable/disable the deployment for a specific deploy environment, AWS Account ID, and AWS Region combination. Can also be set as a static boolean value.
Anything defined here is merged with the value of
deployment.environments. Values defined here take precedence.Example
deployments: - modules: - environments: dev: True test: 123456789012 qa: us-east-1 prod: - 123456789012/ca-central-1 - us-west-2 - 234567890123
using a lookup as the valuedeployments: - modules: - environments: ${var environments} variables: environments: dev: True
Changed in version 1.4.0: Now acts as an explicit toggle for deploying modules to a set AWS Account/AWS Region. For passing values to a module,
deployment.parameters/module.parametersshould be used instead.Changed in version 2.0.0: If defined and the current deploy environment is missing from the definition, processing will be skipped.
- name: Optional[str]
The name of the module to be displayed in logs and the interactive selection menu.
If a name is not provided, the
pathvalue is used.Example
deployments: - modules: - name: networking
- options: Optional[Union[Dict[str, Any], str]] = {}
Options that are passed directly to the module type handler class.
The options that can be used with each module vary. For detailed information about options for each type of module, see Module Configurations.
Anything defined here is merged with the value of
deployment.module_options. Values defined here take precedence.Example
deployments: - module: - options: example: value
using a lookup as the valuedeployments: - module: - options: example: ${var example} variables: example: value
using a lookup in the valuedeployments: - module: - options: ${var parameters} variables: parameters: example: value
- parallel: Optional[List[module]] = []
List of module definitions that can be executed asynchronously.
Incompatible with
class_path,path, andtype.Asynchronous deployment only takes effect when running non-interactively. Otherwise processing will occur synchronously.
Example
deployments: - modules: - parallel: - path: sampleapp-01.cfn - path: sampleapp-02.cfn
- parameters: Optional[Union[Dict[str, Any], str]] = {}
Used to pass variable values to modules in place of an environment configuration file.
Anything defined here is merged with the value of
deployment.parameters. Values defined here take precedence.Example
using a lookup as the valuedeployments: - modules: - parameters: namespace: example-${env DEPLOY_ENVIRONMENT}
using a lookup in the valuedeployments: - modules: - parameters: ${var parameters.${env DEPLOY_ENVIRONMENT}} variables: parameters: dev: namespace: example-dev
New in version 1.4.0.
- path: Optional[Union[str, Path]]
Directory (relative to the Runway config file) containing IaC. The directory can either be on the local file system or a network accessible location.
See path for more detailed information.
Example
using a lookupdeployments: - modules: - path: sampleapp-${env DEPLOY_ENVIRONMENT}.cfn
New in version 1.4.0.
- tags: Optional[List[str]] = []
A list of strings to categorize the module which can be used with the CLI to quickly select a group of modules.
This field is only used by the
--tagCLI option.Example
deployments: - modules: - tags: - app:sampleapp - type:network
- type: Optional[str]
Explicitly define the type of IaC contained within the directory. This can be useful when Runway fails to automatically determine the correct module type.
Accepted Values
cdk
cloudformation
kubernetes
serverless
terraform
static
Example
deployments: - modules: - type: static
New in version 1.4.0.
path
path can either be defined as a local path relative to the Runway config file or a network accessible (remote) location.
When the value is identified as a remote location, Runway is responsible for retrieving resources from the location and caching them locally for processing. This allows the remote resources to be handled automatically by Runway rather than needing to manually retrieve them or employ another mechanism to retrieve them.
Remote Location Syntax
The syntax is based on that of Terraform module sources.
${source}::${uri}//${location}?${arguments}
- source
Combined with the following
::separator, it is used to identify the location as remote. The value determines how Runway with handle retrieving resources from the remote location.- uri
The uniform resource identifier when targeting a remote resource. This instructs runway on where to retrieve your module.
- location
An optional location within the remote location (assessed after the resources have been retrieve) relative to the root of the retrieve resources.
This field is preceded by a
//. If not defining a location, this separator does not need to be provided.- arguments
An optional ampersand (
&) delimited list ofkey=valuepairs that are unique to each remote location source. These are used to provide granular control over how Runway retrieves resources from the remote location.This field is preceded by a
?. If not defining a location, this separator does not need to be provided.
Remote Location Sources
Git Repository
Runway can retrieve a git repository to process modules contained within it. Below is an example of using a module in a git repository as well as a breakdown of the values being provided to each field.
deployments:
- modules:
# ${source}::${uri}//${location}?${arguments}
- path: git::git://github.com/foo/bar.git//my/path?branch=develop
Field |
Value |
Description |
|---|---|---|
source |
|
The type of remote location source. |
uri |
|
The protocol and URI address of the git repository. |
location |
|
The relative path from the root of the repo where
the module is located. (optional)
|
arguments |
|
After cloning the repository, checkout the develop
branch. (optional)
|
Arguments
- branch
Name of a branch to checkout after cloning the git repository.
Only one of branch, commit, or tag can be defined. If none are defined, HEAD is used.
- commit
After cloning the git repository, reset HEAD to the given commit hash.
Only one of branch, commit, or tag can be defined. If none are defined, HEAD is used.
- tag
After cloning the git repository, reset HEAD to the given tag.
Only one of branch, commit, or tag can be defined. If none are defined, HEAD is used.
Test
- class test
Tests can be defined as part of the Runway config file. This is to remove the need for complex Makefiles or scripts to initiate test runners. Simply define all tests for a project in the Runway config file and use the test command to execute them.
Lookup Support
Note
Runway does not set
AWS_REGIONorAWS_DEFAULT_REGIONenvironment variables when using the test command.The following fields support lookups:
- args: Optional[Union[Dict[str, Any], str]] = {}
Arguments to be passed to the test. Supported arguments vary by test type. See Build-in Test Types for the arguments supported by each test type.
Example
tests: - args: commands: - echo "Hello world"
- name: Optional[str]
Name of the test. Used to more easily identify where different tests begin/end in the logs and to identify which tests failed.
Example
tests: - name: example-test
- required: bool = false
Whether the test must pass for subsequent tests to be run. If
false, testing will continue if the test fails.If the test fails, the test command will always return a non-zero exit code regardless of this value.
Example
using a literal valuetests: - required: false
using a lookuptests: - required: ${var test.required} variables: test: required: false
Lookups
Runway Lookups allow the use of variables within the Runway config file. These variables can then be passed along to deployments, modules and tests.
The syntax for a lookup is ${<lookup-name> <query>::<arg>=<arg-val>}.
Component |
Description |
|---|---|
|
Signifies the opening of the lookup. |
|
The name of the lookup you wish to use
(e.g.
env).This signifies the source of the data to
be retrieved by the lookup.
|
The separator between lookup name a query. |
|
|
The value the lookup will be looking for
(e.g.
AWS_REGION).When using a lookup on a dictionary/mapping,
like for the var,
you can get nested values by providing the
full path to the value (e.g.
ami.dev). |
|
The separator between a query and optional arguments. |
|
An argument passed to a lookup.
Multiple arguments can be passed to a lookup
by separating them with a
comma (
,).Arguments are optional.
Supported arguments depend on the lookup being
used.
|
Lookups can be nested (e.g. ${var ami_id.${var AWS_REGION}}).
Lookups can’t resolve other lookups.
For example, if i use ${var region} in my Runway config file to resolve the region from my variables file, the value in the variables file can’t be ${env AWS_REGION}.
Well, it can but it will resolve to the literal value provided, not an AWS region like you may expect.
Lookup Arguments
Arguments can be passed to Lookups to effect how they function.
To provide arguments to a Lookup, use a double-colon (::) after the query.
Each argument is then defined as a key and value separated with equals (=) and the arguments themselves are separated with a comma (,).
The arguments can have an optional space after the comma and before the next key to make them easier to read but this is not required.
The value of all arguments are read as strings.
Example
${var my_query::default=true, transform=bool}
${env MY_QUERY::default=1,transform=bool}
Each Lookup may have their own, specific arguments that it uses to modify its functionality or the value it returns. There is also a common set of arguments that all Lookups accept.
Common Lookup Arguments
- default: Any
If the Lookup is unable to find a value for the provided query, this value will be returned instead of raising an exception.
- get: str
Can be used on a dictionary type object to retrieve a specific piece of data. This is executed after the optional
loadstep.
- indent: int
Number of spaces to use per indent level when transforming a dictionary type object to a string.
- load: Literal['json', 'troposphere', 'yaml']
Load the data to be processed by a Lookup using a specific parser. This is the first action taking on the data after it has been retrieved from it’s source. The data must be in a format that is supported by the parser in order for it to be used.
- json
Loads a JSON serializable string into a dictionary like object.
- troposphere
Loads the
propertiesof a subclass oftroposphere.BaseAWSObjectinto a dictionary.- yaml
Loads a YAML serializable string into a dictionary like object.
- region: str
AWS region used when creating a
boto3.Sessionto retrieve data. If not provided, the region currently being processed will be used. This can be specified to always get data from one region regardless of region is being deployed to.
- transform: Literal['bool', 'str']
Transform the data that will be returned by a Lookup into a different data type. This is the last action taking on the data before it is returned.
Supports the following:
- bool
Converts a string or boolean value into a boolean.
- str
Converts any value to a string. The original data type determines the end result.
list,set, andtuplewill become a comma delimited listdictand anything else will become an escaped JSON string.
Example
deployments:
- parameters:
some_variable: ${var some_value::default=my_value}
comma_list: ${var my_list::default=undefined, transform=str}
Built-in Lookups
cfn
Important
The Stack must exist in CloudFormation before the module using this Lookup begins processing to successfully get a value. This means that the Stack must have been deployed by another module, run before the one using this Lookup, or it must have been created external to Runway.
- Query Syntax
<stack-name>.<output-name>[::<arg>=<arg-val>, ...]
Retrieve a value from CloudFormation Stack Outputs.
The query syntax for this lookup is <stack-name>.<output-name>.
When specifying the output name, be sure to use the Logical ID of the output; not the Export.Name.
If the Lookup is unable to find a CloudFormation Stack Output matching the provided query, the default value is returned or an exception is raised to show why the value could be be resolved (e.g. Stack does not exist or output does not exist on the Stack).
New in version 1.11.0.
See also
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/outputs-section-structure.html
Arguments
This Lookup supports all Common Lookup Arguments.
Example
deployments:
- modules:
path: sampleapp.tf
options:
terraform_backend_config:
bucket: ${cfn common-tf-state.TerraformStateBucketName::region=us-east-1}
dynamodb_table: ${cfn common-tf-state.TerraformStateTableName::region=us-east-1}
region: us-east-1
ecr
Retrieve a value from AWS Elastic Container Registry (ECR).
This Lookup only supports very specific queries.
New in version 1.18.0.
Supported Queries
login-password
Get a password to login to ECR registry.
The returned value can be passed to the login command of the container client of your preference, such as the CFNgin docker.login. After you have authenticated to an Amazon ECR registry with this Lookup, you can use the client to push and pull images from that registry as long as your IAM principal has access to do so until the token expires. The authorization token is valid for 12 hours.
Arguments
This Lookup does not support any arguments.
Example
deployments:
- modules:
- path: example.cfn
parameters:
ecr_password: ${ecr login-password}
...
env
- Query Syntax
<variable-name>[::<arg>=<arg-val>, ...]
Retrieve a value from an environment variable.
The value is retrieved from a copy of the current environment variables that is saved to the context object.
These environment variables are manipulated at runtime by Runway to fill in additional values such as DEPLOY_ENVIRONMENT and AWS_REGION to match the current execution.
Note
DEPLOY_ENVIRONMENT and AWS_REGION can only be resolved during the processing of a module.
To ensure no error occurs when trying to resolve one of these in a Deployment definition, provide a default value.
If the Lookup is unable to find an environment variable matching the provided query, the default value is returned or a ValueError is raised if a default value was not provided.
New in version 1.4.0.
Arguments
This Lookup supports all Common Lookup Arguments but, the following have limited or no effect:
region
Example
deployment:
- modules:
- path: sampleapp.cfn
parameters:
creator: ${env USER}
env_vars:
ENVIRONMENT: ${env DEPLOY_ENVIRONMENT::default=default}
random.string
- Query Syntax
<desired-length>[::<arg>=<arg-val>, ...]
Generate a random string of the given length.
New in version 2.2.0.
Arguments
- digits: bool = True
When generating the random string, the string may contain digits (
[0-9]). If the string can contain digits, it will always contain at least one.
- lowercase: bool = True
When generating the random string, the string may contain lowercase letters (
[a-z]). If the string can contain lowercase letters, it will always contain at least one.
- punctuation: bool = False
When generating the random string, the string may contain ASCII punctuation (
[!"#$%&'()*+,-./:;<=>?@[\]^_`{|}~]). If the string can contain ASCII punctuation, it will always contain at least one.
- uppercase: bool = True
When generating the random string, the string may contain uppercase letters (
[A-Z]). If the string can contain uppercase letters, it will always contain at least one.
This Lookup supports all Common Lookup Arguments but, the following have limited or no effect:
default
get
indent
load
region
Example
This example shows the use of this lookup to create an SSM parameter that will retain value generated during the first deployment. Even through subsequent deployments generate a new value that is passed to the hook, the hook does not overwrite the value of an existing parameter.
pre_deploy: &hooks
- path: runway.cfngin.hooks.ssm.parameter.SecureString
args:
name: /${namespace}/password
overwrite: false
value: ${random.string 12::punctuation=true}
post_destroy: *hooks
ssm
- Query Syntax
<parameter>[::<arg>=<arg-val>, ...]
Retrieve a value from SSM Parameter Store.
If the Lookup is unable to find an SSM Parameter matching the provided query, the default value is returned or ParameterNotFound is raised if a default value is not provided.
Parameters of type SecureString are automatically decrypted.
Parameters of type StringList are returned as a list.
New in version 1.5.0.
Arguments
This Lookup supports all Common Lookup Arguments.
Example
deployment:
- modules:
- path: sampleapp.cfn
parameters:
secret_value: ${ssm /example/secret}
conf_file: ${ssm /example/config/json::load=json, get=value}
toggle: ${ssm toggle::load=yaml, get=val, transform=bool}
env_vars:
SOME_VARIABLE: ${ssm /example/param::region=us-east-1}
DEFAULT_VARIABLE: ${ssm /example/default::default=default}
var
- Query Syntax
<variable-name>[::<arg>=<arg-val>, ...]
Retrieve a variable from the variables file or definition.
If the Lookup is unable to find an defined variable matching the provided query, the default value is returned or a ValueError is raised if a default value was not provided.
Nested values can be used by providing the full path to the value but, it will not select a list element.
The returned value can contain any YAML support data type (dictionaries/mappings/hashes, lists/arrays/sequences, strings, numbers, and boolean).
New in version 1.4.0.
Arguments
This Lookup supports all Common Lookup Arguments but, the following have limited or no effect:
region
Example
deployment:
- modules:
- path: sampleapp.cfn
parameters:
ami_id: ${var ami_id.${env AWS_REGION}}
env_vars:
SOME_VARIABLE: ${var some_variable::default=default}
Defining Tests
Tests can be defined in the runway config file to test your modules in any way you desire before deploying.
They are run by using the runway test command.
Tests are run in the order they are defined.
Example:
tests:
- name: example-test
type: script
args:
commands:
- echo "Success!"
Test Failures
The default behavior if a test failed is to continue running the rest of the tests and return a non-zero exit code at the end.
This behavior can be modified to stop testing on failure by setting required: true in the test definition.
This will terminate execution if a test fails; no further tests will be run.
Example
tests:
- name: hello-world
type: script
required: true
args:
commands:
- echo "Hello World!" && exit 1
Built-in Test Types
cfn-lint
- Source Tool
- Description
Validate CloudFormation yaml/json templates against the CloudFormation spec and additional checks. Includes checking valid values for resource properties and best practices.
In order to use this test, there must be a .cfnlintrc file in the same directory as the Runway config file.
Example:
tests:
- name: cfn-lint-example
type: cfn-lint
script
Executes a list of provided commands. Each command is run in its own subprocess.
Commands are passed into the test using the commands argument.
Example:
tests:
- name: hello-world
type: script
args:
commands:
- echo "Hello World!"
yamllint
- Source Tool
- Description
A linter for YAML files. yamllint does not only check for syntax validity, but for weirdnesses like key repetition and cosmetic problems such as lines length, trailing spaces, indentation, etc.
A .yamllint file can be placed at in the same directory as the
Runway config file to customize the linter or,
the Runway provided template will be used.
Example:
tests:
- name: yamllint-example
type: yamllint
Repo Structure
Projects deployed via Runway can be structured in a few ways.
Contents
Git Branches as Environments
This example shows two modules using environment git branches (these same files would be present in each environment branch, with changes to any environment promoted through branches).
.
├── myapp.cfn
│ ├── dev-us-west-2.env
│ ├── prod-us-west-2.env
│ ├── myapp.yaml
│ └── templates
│ └── foo.json
├── myapp.tf
│ ├── backend.tfvars
│ ├── dev-us-east-1.tfvars
│ ├── prod-us-east-1.tfvars
│ └── main.tf
└── runway.yml
Directories as Environments
The same two modules from the above Git Branches as Environments structure can instead be stored in a normal single-branch git repo. Each directory correlates with an environment (dev and prod in this example).
Environment changes are done by copying the environments’ contents between each other.
E.g., promotion from dev to prod could be as simple as diff -u dev/ prod/ followed by rsync -r --delete dev/ prod/
Enabling that automated promotion is one of the reasons this example below has prod config files in the dev folder and vice versa. When promotions between environments are more hand managed, this is not technically required.
.
├── dev
│ ├── myapp.cfn
│ │ ├── dev-us-west-2.env
| │ ├── prod-us-west-2.env
│ │ ├── myapp.yaml
│ │ └── templates
│ │ └── myapp_cf_template.json
│ ├── myapp.tf
│ │ ├── backend.tfvars
│ │ ├── dev-us-east-1.tfvars
| │ ├── prod-us-east-1.tfvars
│ │ └── main.tf
│ └── runway.yml
└── prod
├── myapp.cfn
│ ├── dev-us-west-2.env
│ ├── prod-us-west-2.env
│ ├── myapp.yaml
│ └── templates
│ └── myapp_cf_template.json
├── myapp.tf
│ ├── backend.tfvars
│ ├── dev-us-east-1.tfvars
│ ├── prod-us-east-1.tfvars
│ └── main.tf
└── runway.yml
Directories as Environments with a Single Module
Another sample repo structure, showing environment folders containing a single CloudFormation modules at their root (using the ignore_git_branch Runway config file field and a single declared module of ./ to merge the Environment & Module folders).
See the Directories as Environments example above for more information on why this shows prod config files in the dev folder and vice versa.
.
├── dev
│ ├── dev-us-west-2.env
│ ├── prod-us-west-2.env
│ ├── myapp.yaml
│ ├── runway.yml
│ └── templates
│ └── myapp_cf_template.json
└── prod
├── dev-us-west-2.env
├── prod-us-west-2.env
├── myapp.yaml
├── runway.yml
└── templates
└── myapp_cf_template.json
Module Configuration
AWS Cloud Development Kit (CDK)
The CDK module type is deployed using the AWS Cloud Development Kit (CDK). Runway uses system installed npm to install the CDK per-module. This means that the CDK must be included as a dev dependency in the package.json of the module.
Configuration
Standard CDK rules apply but, we have some added prerequisites, recommendations, and caveats.
Contents
Prerequisites
CDK must be a dev dependency of the module (e.g.
npm install --save-dev aws-cdk)
We strongly recommend you commit the package-lock.json that is generated after running npm install.
Recommendations
Feature Flags
The AWS CDK uses feature flags to enable potentially breaking behaviors prior to the next major release that makes them default behaviors.
Flags are stored as Runtime context values in cdk.json (or ~/.cdk.json).
This feature flag is available in version ^1.0.0.
If this is set to true (recommend), cdk diff will always exit with 0.
With this set to false, cdk diff will exit with a non-zero exit code if there is a diff.
This will result in Runway exiting before all stacks/modules/deployments are processed.
Example
{
"context": {
"aws-cdk:enableDiffNoFail": true
},
}
Environments
Unlike some other module types, CDK does not have a file that can be used to configure an environment.
It can only be configured using the deployment.environments/module.environments field.
Example
deployments:
- modules:
- path: mycdkmodule.cdl
environments:
dev: true
prod: true
- modules:
- path: myothercdkmodule.cdk
environments:
dev: true
prod: true
Options
- build_steps: Optional[List[str]] = None
Shell commands to be run before processing the module.
See Build Steps for more details.
Example
options: build_steps: - npx tsc
- skip_npm_ci: bool = False
Skip running
npm ciin the module directory prior to processing the module. See Disable NPM CI for more details.Example
options: skip_npm_ci: true
Directory Structure
Example directory structures for a CDK module.
C# Example
.
├── add-project.hook.d.ts
├── cdk.json
├── package.json
├── package-lock.json
└── src
├── HelloCdk
│ ├── HelloCdk.csproj
│ ├── HelloConstruct.cs
│ ├── HelloStack.cs
│ └── Program.cs
└── HelloCdk.sln
Python Example
.
├── app.py
├── cdk.json
├── hello
│ ├── __init__.py
│ ├── hello_construct.py
│ └── hello_stack.py
├── package.json
├── package-lock.json
├── poetry.lock
└── pyproject.toml
TypeScript Example
.
├── bin
│ └── sample.ts
├── cdk.json
├── lib
│ └── sample-stack.ts
├── package.json
├── package.json
└── tsconfig.json
Advanced Features
Advanced features and detailed information for using CDK with Runway.
Contents
Build Steps
Build steps (e.g. for compiling TypeScript) can be specified in deployment.module_options/module.options.
These steps will be run before each diff, deploy, or destroy.
Example
deployments:
- modules:
- path: mycdkmodule.cdk
environments:
dev: true
options:
build_steps:
- npx tsc
Disabling NPM CI
At the start of each module execution, Runway will execute npm ci to ensure that CDK is installed in the project (so Runway can execute it via npx cdk).
This can be disabled (e.g. for use when the node_modules directory is pre-compiled) via the skip_npm_ci field of deployment.module_options/module.options.
Example
deployments:
- modules:
- path: mycdkmodule.cdk
options:
skip_npm_ci: true
CloudFormation & Troposphere
The CloudFormation module type is deployed using Runway’s CloudFormation engine (CFNgin). It is able to deploy raw CloudFormation templates (JSON & YAML) and Troposphere templates that are written in the form of a Blueprints.
Configuration
In addition to the Runway Config File, there are two files that can be used for configuration:
a YAML configuration file [REQUIRED]
a key/value environment file
Changed in version 1.5.0: Stacker is no longer used for handling CloudFormation/Troposphere. It has been replaced with an internal CloudFormation engin (CFNgin).
Contents
runway.yml
Example
deployments:
- modules:
- path: sampleapp.cfn
type: cloudformation # not required; implied from ".cfn" directory extension
environments:
dev: true
parameters:
namespace: example-${env DEPLOY_ENVIRONMENT}
cfngin_bucket: example-${env DEPLOY_ENVIRONMENT}-${env AWS_REGION}
regions:
- us-east-1
Options
CloudFormation modules do not have any module-specific options.
Parameters
Runway can pass Parameters to a CloudFormation module in place of or in addition to values in an environment file.
When Parameters are passed to the module, the data type is retained (e.g. array, boolean, mapping).
A typical usage pattern would be to use Runway Lookups in combination with Parameters to pass deploy environment and/or region specific values to the module from the Runway Config File.
Example
deployments:
- modules:
- sampleapp-01.cfn
- path: sampleapp-02.cfn
parameters:
instance_count: ${var instance_count.${env DEPLOY_ENVIRONMENT}}
parameters:
image_id: ${var image_id.%{env AWS_REGION}}
Runway automatically makes the following commonly used Parameters available to CloudFormation modules.
Note
If these parameters are already being explicitly defined in deployment.parameters/module.parameters the value provided will be used instead of what would be automatically added.
- environment: str
Taken from the
DEPLOY_ENVIRONMENTenvironment variable. This will the be current deploy environment.
- region: str
Taken from the
AWS_REGIONenvironment variable. This will be the current region being processed.
CFNgin Config File
The CFNgin config file has full support for YAML features like anchors & references for a DRY config file (See YAML anchors & references for details).
Top-Level Fields
- class cfngin.config
Runway’s CFNgin makes use of a YAML formatted config file to define the different CloudFormation stacks that make up a given environment.
- cfngin_bucket: Optional[str] = None
By default, CloudFormation templates are pushed into an S3 bucket and CloudFormation is pointed to the template in that bucket when launching or updating stacks. By default it uses a bucket named
cfngin-${namespace}-${region}, where the namespace isnamespaceand region is the current AWS region.To change this, define a value for this field.
If the bucket does not exists, CFNgin will try to create it in the same region that the stacks will be launched in. The bucket will be created by deploying a CloudFormation stack named
${namespace}-cfngin-bucketwhere the namespace isnamespace. If there is a stack namedcfngin-bucketfound defined in thestacksfield, it will be used in place of defaultstack& Blueprint (runway.cfngin.blueprints.cfngin_bucket.CfnginBucket) provided by CFNgin. When using a custom stack, it is the user’s responsibility to ensure that a bucket with the correct name is created by this stack.If you want CFNgin to upload templates directly to CloudFormation instead of first uploading to S3, you can set this field to an empty string. However, the template size is greatly limited when uploading directly. See the CloudFormation Limits Reference.
Tip
Defining a
stackthat uses the Blueprint provided by CFNgin allows for easy customization of stack fields such astags. It also allows the stack to be deleted as part of the normal deletion process. If it is not defined as a stack, CFNgin won’t delete the stack or bucket.namespace: ${namespace} cfngin_bucket: cfngin-${namespace}-${region} stacks: - name: cfngin-bucket class_path: runway.cfngin.blueprints.cfngin_bucket.CfnginBucket variables: BucketName: cfngin-${namespace}-${region} pre_destroy: - path: runway.cfngin.hooks.cleanup_s3.purge_bucket args: bucket_name: cfngin-${namespace}-${region}
Example
cfngin_bucket: example-${region}
Changed in version 2.0.0: The format of the default value is now
cfngin-${namespace}-${region}.
- cfngin_bucket_region: Optional[str] = None
AWS Region where
cfngin_bucketis located. This can be different than the region currently being deployed to but, ensure to account for all AWS limitations before manually setting this value.If not provided, the current region is used.
Example
cfngin_bucket_region: us-east-1
- cfngin_cache_dir: Optional[str] = ./.runway/
Path to a local directory that CFNgin will use for local caching.
If provided, the cache location is relative to the CFNgin configuration file.
If NOT provided, the cache location is relative to the
runway.yaml/runway.ymlfile and is shared between all Runway modules.Example
cfngin_cache_dir: ./.runway
- log_formats: Optional[Dict[str, str]] = {}
Customize log message formatting by log level.
Any of the standard Python logging module format attributes can be used when writing a new log format string.
Example
log_formats: info: "[%(asctime)s] %(message)s" debug: "[%(asctime)s] %(levelname)s %(threadName)s %(name)s:%(lineno)d(%(funcName)s): %(message)s"
- lookups: Optional[Dict[str, str]] = {}
Lookups allow you to create custom methods which take a value and are resolved at runtime time. The resolved values are passed to the
Blueprintbefore it is rendered. For more information, see the Lookups documentation.CFNgin provides some common Lookups, but it is sometimes useful to have your own custom lookup that doesn’t get shipped with Runway. You can register your own lookups here.
The key of each item in the mapping will be used as the name of the lookup type when registering the lookup. The value should be the path to a valid lookup handler.
Example
lookups: custom: path.to.lookup.handler conf_value: ${custom query}
- mappings: Optional[Dict[str, Dict[str, Dict[str, Any]]]] = {}
Mappings are dictionaries that are provided as Mappings to each CloudFormation stack that CFNgin produces.
These can be useful for providing things like different AMIs for different instance types in different regions.
These can be used in each
Blueprint/template as usual.Example
mappings: AmiMap: us-east-1: NAT: ami-ad227cc4 ubuntu1404: ami-74e27e1c bastion: ami-74e27e1c us-west-2: NAT: ami-290f4119 ubuntu1404: ami-5189a661 bastion: ami-5189a661
- namespace: str
A namespace to create all stacks within. The value will be used as a prefix for the name of any stack that is created.
In addition, this value can be used to create an S3 bucket that will be used to upload and store all CloudFormation templates. See
cfngin_bucketfor more detailed information.In general, this is paired with the concept of deploy environments to create a namespace per environment.
Example
namespace: ${namespace}-${environment}
- namespace_delimiter: Optional[str] = "-"
By default,
-will be used as a delimiter between thenamespaceand the declared stack name to deploy the actual CloudFormation stack name that gets created.If you prefer to not use a delimiter, an empty string can be used as the value of this field.
See the CloudFormation API Reference for allowed stack name characters
Example
namespace_delimiter: ""
- package_sources: Optional[cfngin.package_sources] = {}
See Remote Sources for detailed information.
package_sources: git: ... local: ... s3: ...
- persistent_graph_key: Optional[str] = None
Used to track the state of stacks defined in configuration file. This can result in stacks being destroyed when they are removed from the configuration file removing the need to manually delete the stacks.
See Persistent Graph for detailed information.
Example
persistent_graph_key: unique-key.json
- post_deploy: Optional[List[cfngin.hook]] = []
Python functions/methods that are executed after processing the stacks in the config while using the deploy command.
See Hooks for more detailed information.
Example
post_deploy: - path: do.something
Changed in version 2.0.0: post_build renamed to post_deploy.
Changed in version 2.2.0: The CFNgin bucket is now created using a CloudFormation stack.
- post_destroy: Optional[List[cfngin.hook]] = []
Python functions/methods that are executed after processing the stacks in the config while using the destroy command.
See Hooks for more detailed information.
Example
post_destroy: - path: do.something
- pre_deploy: Optional[List[cfngin.hook]] = []
Python functions/methods that are executed before processing the stacks in the config while using the deploy command.
See Hooks for more detailed information.
Example
pre_deploy: - path: do.something
Changed in version 2.0.0: pre_build renamed to pre_deploy.
- pre_destroy: Optional[List[cfngin.hook]] = []
Python functions/methods that are executed before processing the stacks in the config while using the destroy command.
See Hooks for more detailed information.
Example
pre_destroy: - path: do.something
- service_role: Optional[str] = None
By default CFNgin doesn’t specify a service role when executing changes to CloudFormation stacks. If you would prefer that it do so, you define the IAM Role ARN that CFNgin should use when executing CloudFormation changes.
This is the equivalent of setting
RoleARNon a call to the following CloudFormation API calls:CreateStack,UpdateStack,CreateChangeSet.See the AWS CloudFormation service role for more information.
Example
service_role: arn:aws:iam::123456789012:role/name
- stacks: Optional[List[cfngin.stack]] = []
This is the core part of the config where the CloudFormations stacks that will be deployed in the environment are defined.
See Stack for more information.
- sys_path: Optional[str] = None
A path to be added to
$PATHwhile processing the configuration file. This will allow modules from the provided path location to be used.When setting
class_pathfor aBlueprintorpathfor ahook, it is sometimes desirable to load modules from outside the default$PATH(e.g. to include modules inside the same repo as config files).Example
sys_path: ./ # most common value to use
- tags: Optional[Dict[str, str]] = {"cfngin_namespace": namespace}
A dictionary of tags to add to all stacks. These tags are propagated to all resources that AWS CloudFormation supports. See CloudFormation - Resource Tag for more information.
If this field is undefined, a cfngin_namespace tag is applied to your stack with the value of
namespaceas the tag-value. Alternatively, this field can be set to a value of{}(an empty dictionary) to disable the default tag.Example
tags: namespace: ${namespace} example: value
disable default tagtags: {}
Stack
- class cfngin.stack
Defines a CloudFormation stack.
Lookup Support
The following fields support lookups:
Example
stacks: - name: vpc-example class_path: blueprints.vpc.VPC variables: InstanceType: t2.small SshKeyName: default ImageName: NAT AZCount: 2 PublicSubnets: - 10.128.0.0/24 - 10.128.1.0/24 - 10.128.2.0/24 - 10.128.3.0/24 PrivateSubnets: - 10.128.8.0/22 - 10.128.12.0/22 - 10.128.16.0/22 - 10.128.20.0/22 CidrBlock: 10.128.0.0/16
- class_path: Optional[str] = None
A python importable path to the
Blueprintclass to be used.Exactly one of
class_pathortemplate_pathmust be defined.Example
stacks: - name: example-stack class_path: example.BlueprintClass
- description: Optional[str] = None
A short description to apply to the stack. This overwrites any description defined in the
Blueprint. See Cloudformation - Template Description for more information.Example
stacks: - name: example-stack description: An Example Stack
- enabled: Optional[bool] = True
Whether to deploy/update the stack. This enables the ability to disable stacks in different environments.
Important
This field is ignored when destroying stacks.
Example
stacks: - name: example-stack enabled: false - name: another-stack enabled: ${enable_another_stack}
- in_progress_behavior: Optional[Literal['wait']] = None
Specifies the behavior for when a stack is in
CREATE_IN_PROGRESSorUPDATE_IN_PROGRESS. By default, CFNgin will raise an exception if the stack is in anIN_PROGRESSstate when processing begins.If the value of this field is wait, CFNgin will wait for the previous update to complete before attempting to update the stack instead of raising an exception.
Example
stacks: - name: example-stack in_progress_behavior: wait
- locked: Optional[bool] = False
Whether the stack should be updated after initial deployment. This is useful for risky stacks that you don’t want to take the risk of allowing CloudFormation to update but still want to deploy it using CFNgin.
Example
stacks: - name: example-stack locked: true - name: another-stack locked: ${locked_another_stack}
- name: str
Name of the CFNgin Stack. The value of this field is used by CFNgin when referring to a Stack. It will also be used as the name of the Stack when created in CloudFormation unless overridden by
stack_name.Note
namespacewill be appended to this value when used as the name of the CloudFormation Stack.Example
stacks: - name: example-stack
- protected: Optional[bool] = False
Whether to force all updates to be performed interactively.
When true and running in non-interactive mode, CFNgin will switch to interactive mode for this stack to require manual review and approval of any changes.
Example
stacks: - name: example-stack protected: true - name: another-stack protected: ${protected_another_stack}
- required_by: Optional[List[str]] = []
A list of other stacks that require this stack. All stacks must be defined in the same configuration file.
Inverse of
requires.Example
stacks: - name: example-stack: # deployed first required_by: - another-stack - name: another-stack: # deployed after example-stack ...
- requires: Optional[List[str]] = []
A list of other stacks that this stack requires. All stacks must be defined in the same configuration file.
Inverse of
required_by.Example
stacks: - name: example-stack# deployed after another-stack requires: - another-stack - name: another-stack # deployed first ...
- stack_name: Optional[str] = None
The name used when creating the CloudFormation stack. If not provided,
namewill be used.Note
namespacewill be appended to this value.Example
stacks: - name: example-stack stack_name: another-name
- stack_policy_path: Optional[str] = None
Path to a JSON formatted stack policy that will be applied when the CloudFormation stack is created and/or updated.
See CloudFormation - Prevent updates to stack resources for examples and more information.
Example
stacks: - name: example-stack stack_policy_path: ./stack_policies/example-stack.json
- tags: Optional[Dict[str, str]] = {}
A dictionary of tags to add to the Stack. These tags are propagated to all resources that AWS CloudFormation supports. See CloudFormation - Resource Tag for more information.
This will be combined with the global
tags. Values defined here take precedence over those defined globally.Example
stacks: - name: example-stack tags: namespace: ${namespace} example: value
- template_path: Optional[str]
Path to a raw CloudFormation template (JSON or YAML). Can be relative to the working directory (e.g. templates stored alongside the configuration file), or relative to a directory in the $PATH (i.e. for loading templates retrieved via
package_sources).Exactly one of
class_pathortemplate_pathmust be provided.Example
stacks: - name: example-stack template_path: ./templates/example-stack.yml - name: another-stack template_path: remote/path/templates/another-stack.json
- termination_protection: Optional[bool] = False
Whether the stack will be protected from termination by CloudFormation.
Any attempts to destroy the stack (using Runway, the AWS console, AWS API, etc) will be prevented unless manually disabled.
When updating a stack and the value has been changed, termination protection on the CloudFormation stack sill also change. This is useful when needing to destroy a stack by first changing the value in the configuration file, updating the stack, then proceeding to destroy it.
Example
stacks: - name: example-stack termination_protection: true - name: another-stack termination_protection: ${termination_protection_another_stack}
- timeout: Optional[int] = None
Specifies the amount of time, in minutes, that CloudFormation should allot before timing out stack creation operations. If CloudFormation can’t create the entire stack in the time allotted, it fails the stack creation due to timeout and rolls back the stack.
By default, there is no timeout for stack creation. However, individual resources may have their own timeouts based on the nature of the service they implement. For example, if an individual resource in your stack times out, stack creation also times out even if the timeout you specified for stack creation hasn’t yet been reached.
Example
stacks: - name: example-stack timeout: 120
- variables: Optional[Dict[str, Any]] = {}
A dictionary of Variables to pass to the
Blueprintwhen rendering the CloudFormation template. Can be any valid YAML data structure.When using a raw CloudFormation template, these are the values provided for it’s Parameters.
Example
stacks: - name: example-stack variables: StackVariable: value
Variables
Variables are values that will be passed into a Blueprint before it is rendered.
Variables can be any valid YAML data structure and can leverage Lookups to expand values at runtime.
If you have a common set of variables that you need to pass around in many places, it can be annoying to have to copy and paste them in multiple places. Instead, using a feature of YAML known as anchors & references, you can define common values in a single place and then refer to them with a simple syntax.
For example, say you pass a common domain name to each of your stacks, each of them taking it as a Variable. Rather than having to enter the domain into each stack you could do the following to have an anchor called domain that you can use in place of any value in the config to provide the value mydomain.com.
stacks:
- name: example-stack
class_path: blueprints.Example
variables:
DomainName: &domain mydomain.com
- name: vpc
class_path: blueprints.VPC
variables:
DomainName: *domain
Even more powerful is the ability to anchor entire dictionaries, and then reference them in another dictionary, effectively providing it with default values. Now, rather than having to provide each of those variables to every stack that could use them, you can just do this instead.
stacks:
- name: example-stack
class_path: blueprints.Example
variables: &variables
DomainName: mydomain.com
InstanceType: m3.medium
AMI: ami-12345abc
- name: vpc
class_path: blueprints.VPC
variables:
<< : *variables
InstanceType: c4.xlarge # override the InstanceType in this stack
Since CFNgin encourages the breaking up of your CloudFormation stacks into entirely separate stacks, sometimes you’ll need to pass values from one stack to another.
The way this is handled in CFNgin is by having one stack provide Outputs for all the values that another stack may need, and then using those as the inputs for another stack’s variables.
CFNgin makes this easier for you by providing a syntax for variables that will cause CFNgin to automatically look up the values of Outputs from another stack in its config.
To do so, use the output in the variables on the target stack.
MyParameter: ${output OtherStack.OutputName}
For more information see Lookups.
In this example config, when deploying things inside a VPC, you will need to pass the VpcId of the VPC that you want the resources to be located in. If the vpc stack provides an Output called VpcId, you can reference it easily.
domain_name: my_domain &domain
stacks:
- name: vpc
class_path: blueprints.vpc.VPC
variables:
DomainName: *domain
- name: webservers
class_path: blueprints.asg.AutoscalingGroup
variables:
DomainName: *domain
VpcId: ${output vpc.VpcId} # gets the VpcId Output from the vpc stack
Doing this creates an implicit dependency from the webservers stack to the vpc stack, which will cause CFNgin to submit the vpc stack, and then wait until it is complete until it submits the webservers stack.
This would be the same as adding vpc to the requires field of the webservers stack.
Environment File
When using CFNgin, you can optionally provide an “environment” file.
The CFNgin config file will be interpolated as a string.Template using the key-value pairs from the environment file as parameters.
The format of the file is a single key-value per line, separated by a colon (:).
File Naming
Environment files must follow a specific naming format in order to be recognized by Runway. The files must also be stored at the root of the module’s directory.
- ${DEPLOY_ENVIRONMENT}-${AWS_REGION}.env
The typical naming format that will be used for these files specifies the name of the
DEPLOY_ENVIRONMENTandAWS_REGIONin which to use the file.- ${DEPLOY_ENVIRONMENT}.env
The region can optionally be omitted to apply a single file to all regions.
Files following both naming schemes may be used. The file with the most specific name takes precedence.
Values passed in as parameters from the Runway Config File take precedence over those provided in an environment file.
Usage
A pretty common use case is to have separate environments that you want to look mostly the same, though with some slight modifications. For example, you might want a production and a staging environment.
The production environment likely needs more instances, and often those instances will be of a larger instance type.
The parameters defined in an environment file, deployment.parameters, and/or module.parameters allow you to use your existing CFNgin config, but provide different values based on the current deploy environment.
Example
vpcID: vpc-12345678
Provided the key-value pair above, you will now be able to use this in your configs for a deploy environment. They act as keys that can be used in your config file, providing a sort of templating ability. This allows you to change the values of your config based on the current deploy environment.
For example, if you have a webserver stack, and you need to provide it a variable for the instance size it should use, you would have something like this in your config file.
stacks:
- name: webservers
class_path: blueprints.asg.AutoscalingGroup
variables:
InstanceType: m3.medium
But what if you needed more CPU in your production environment, but not in your staging?
Without parameters, you’d need a separate config for each.
With parameters, you can simply define two different values for InstanceType in an an environment file, deployment.parameters, and/or module.parameters then use the parameter’s name to reference the value in a config file.
# in your config file:
stacks:
- name: webservers:
class_path: blueprints.asg.AutoscalingGroup
variables:
InstanceType: ${web_instance_type}
Using Environment Files
Both files would be required.
web_instance_type: m5.medium
web_instance_type: c5.xlarge
Using Runway
This option would not required the use of environment files to define the values.
deployments:
- modules:
- name: Sample Application
path: sampleapp.cfn
parameters:
web_instance_type: ${var web_instance_type.${env DEPLOY_ENVIRONMENT}}
variables:
web_instance_type:
stage: m5.medium
prod: c5.xlarge
Directory Structure
Example directory structures for a CloudFormation module.
Blueprints
Important
Blueprints must be importable by python. (e.g. directory contains __init__.py)
.
├── poetry.lock
├── pyproject.toml
├── runway.variables.yml
├── runway.yml
└── sampleapp.cfn
├── blueprints
│ ├── __init__.py
│ └── my_blueprint.py
├── dev-us-east-1.env
└── cfngin.yml
Cloudformation Templates
Important
CloudFormation templates can’t be stored in the root of the module directory. They must be in a subdirectory or external to the module.
.
├── poetry.lock
├── pyproject.toml
├── runway.variables.yml
├── runway.yml
└── sampleapp.cfn
├── templates
│ ├── template-01.yml
│ └── template-02.json
├── dev-us-east-1.env
├── 01-cfngin.yml
└── 02-cfngin.yml
Advanced Features
Advanced features and detailed information for using Runway’s CFNgin for CloudFormation modules.
Blueprints
A Blueprint is a python classes that dynamically builds CloudFormation templates.
Where you would specify a raw Cloudformation template in a stack using the template_path key, you instead specify a Blueprint subclass using the class_path key.
Traditionally Blueprints are built using troposphere, but that is not absolutely necessary.
Making your own should be easy, and you can take a lot of examples from Runway blueprints.
In the end, all that is required is that the Blueprint is a subclass of runway.cfngin.blueprints.base.Blueprint and it has the following method overridden:
# Updates self.template to create the actual template
def create_template(self) -> None:
"""Create a template from the blueprint.
Main method called by CFNgin when rendering a Blueprint into a template
that is expected to be overridden.
"""
Contents
Variables
A Blueprint can define a VARIABLES ClassVar that defines the variables it accepts from the Config Variables.
VARIABLES should be a Dict of <variable name>: <variable definition>.
The variable definition should be a BlueprintVariableTypeDef.
Example
from __future__ import annotations
from typing import TYPE_CHECKING, ClassVar, Dict
from runway.cfngin.blueprints.base import Blueprint
if TYPE_CHECKING:
from runway.cfngin.blueprints.type_defs import BlueprintVariableTypeDef
class ExampleClass(Blueprint):
"""Example Blueprint."""
VARIABLES: ClassVar[Dict[str, BlueprintVariableTypeDef]] = {
"ExampleVariable": {
"default": "",
"description": "Example variable.",
"type": str,
}
}
See also
runway.cfngin.blueprints.type_defs.BlueprintVariableTypeDefDocumentation for the contents of a
Blueprintvariable definition.
Variable Types
Any native python type can be specified as the type for a variable.
You can also use the following custom types:
The TroposphereType can be used to generate resources for use in the Blueprint directly from user-specified configuration.
Which of the below case applies depends on what defined_type was chosen, and how it would be normally used in the Blueprint (and CloudFormation in general).
When defined_type is a Resource Type, the value specified by the user in the configuration file must be a dictionary, but with two possible structures.
When many is disabled, the top-level dictionary keys correspond to parameters of the defined_type constructor.
The key-value pairs will be used directly, and one object will be created and stored in the variable.
When many is enabled, the top-level dictionary keys are resource titles, and the corresponding values are themselves dictionaries, to be used as parameters for creating each of multiple defined_type objects.
A list of those objects will be stored in the variable.
When defined_type is a property type the value specified by the user in the configuration file must be a dictionary or a list of dictionaries.
When many is disabled, the top-level dictionary keys correspond to parameters of the defined_type constructor.
The key-value pairs will be used directly, and one object will be created and stored in the variable.
When many is enabled, a list of dictionaries is expected.
For each element, one corresponding call will be made to the defined_type constructor, and all the objects produced will be stored (also as a list) in the variable.
In either case, when optional is enabled, the variable may have no value assigned, or be explicitly assigned a null value.
When that happens the variable’s final value will be None.
Below is an annotated example:
"""Example Blueprint."""
from __future__ import annotations
from typing import TYPE_CHECKING, ClassVar, Dict
from troposphere import s3, sns
from runway.cfngin.blueprints.base import Blueprint
from runway.cfngin.blueprints.variables.types import TroposphereType
if TYPE_CHECKING:
from runway.cfngin.blueprints.type_defs import BlueprintVariableTypeDef
class Buckets(Blueprint):
"""S3 Buckets."""
VARIABLES: ClassVar[Dict[str, BlueprintVariableTypeDef]] = {
# Specify that Buckets will be a list of s3.Bucket types.
# This means the config should a dictionary of dictionaries
# which will be converted into troposphere buckets.
"Buckets": {
"type": TroposphereType(s3.Bucket, many=True),
"description": "S3 Buckets to create.",
},
# Specify that only a single bucket can be passed.
"SingleBucket": {
"type": TroposphereType(s3.Bucket),
"description": "A single S3 bucket",
},
# Specify that Subscriptions will be a list of sns.Subscription types.
# Note: sns.Subscription is the property type, not the standalone
# sns.SubscriptionResource.
"Subscriptions": {
"type": TroposphereType(sns.Subscription, many=True),
"description": "Multiple SNS subscription designations",
},
# Specify that only a single subscription can be passed, and that it
# is made optional.
"SingleOptionalSubscription": {
"type": TroposphereType(sns.Subscription, optional=True),
"description": "A single, optional SNS subscription designation",
},
}
def create_template(self) -> None:
"""Create a template from the blueprint."""
# The Troposphere s3 buckets have already been created when we
# access self.variables["Buckets"], we just need to add them as
# resources to the template.
for bucket in self.variables["Buckets"]:
self.template.add_resource(bucket)
# Add the single bucket to the template. You can use
# `Ref(single_bucket)` to pass CloudFormation references to the
# bucket just as you would with any other Troposphere type.
self.template.add_resource(self.variables["SingleBucket"])
subscriptions = self.variables["Subscriptions"]
optional_subscription = self.variables["SingleOptionalSubscription"]
# Handle it in some special way...
if optional_subscription is not None:
subscriptions.append(optional_subscription)
self.template.add_resource(
sns.Topic("ExampleTopic", TopicName="Example", Subscriptions=subscriptions)
)
A sample config for the above:
stacks:
- name: buckets
class_path: path.to.above.Buckets
variables:
Buckets:
# resource name (title) that will be added to CloudFormation.
FirstBucket:
# name of the s3 bucket
BucketName: my-first-bucket
SecondBucket:
BucketName: my-second-bucket
SingleBucket:
# resource name (title) that will be added to CloudFormation.
MySingleBucket:
BucketName: my-single-bucket
Subscriptions:
- Endpoint: one-lambda
Protocol: lambda
- Endpoint: another-lambda
Protocol: lambda
# The following could be omitted entirely
SingleOptionalSubscription:
Endpoint: a-third-lambda
Protocol: lambda
The CFNType can be used to signal that a variable should be submitted to CloudFormation as a Parameter instead of only available to the Blueprint when rendering.
This is useful if you want to leverage AWS-Specific Parameter types (e.g. List<AWS::EC2::Image::Id>) or Systems Manager Parameter Store values (e.g. AWS::SSM::Parameter::Value<String>).
See runway.cfngin.blueprints.variables.types for available subclasses of the CFNType.
Example
"""Example Blueprint."""
from __future__ import annotations
from typing import TYPE_CHECKING, ClassVar, Dict
from runway.cfngin.blueprints.base import Blueprint
from runway.cfngin.blueprints.variables.types import (
CFNString,
EC2AvailabilityZoneNameList,
)
if TYPE_CHECKING:
from runway.cfngin.blueprints.type_defs import BlueprintVariableTypeDef
class ExampleBlueprint(Blueprint):
"""Example Blueprint."""
VARIABLES: ClassVar[Dict[str, BlueprintVariableTypeDef]] = {
"String": {"type": str, "description": "Simple string variable"},
"List": {"type": list, "description": "Simple list variable"},
"CloudFormationString": {
"type": CFNString,
"description": "A variable which will create a CloudFormation "
"Parameter of type String",
},
"CloudFormationSpecificType": {
"type": EC2AvailabilityZoneNameList,
"description": "A variable which will create a CloudFormation "
"Parameter of type List<AWS::EC2::AvailabilityZone::Name>",
},
}
def create_template(self) -> None:
"""Create a template from the blueprint."""
# `self.variables` returns a dictionary of <variable name>: <variable value>.
# For the subclasses of `CFNType`, the values are
# instances of `CFNParameter` which have a `ref` helper property
# which will return a troposphere `Ref` to the parameter name.
self.add_output("StringOutput", self.variables["String"])
# self.variables["List"] is a native list
for index, value in enumerate(self.variables["List"]):
self.add_output("ListOutput:{}".format(index), value)
# `CFNParameter` values (which wrap variables with a `type`
# that is a `CFNType` subclass) can be converted to troposphere
# `Ref` objects with the `ref` property
self.add_output(
"CloudFormationStringOutput", self.variables["CloudFormationString"].ref
)
self.add_output(
"CloudFormationSpecificTypeOutput",
self.variables["CloudFormationSpecificType"].ref,
)
Utilizing Stack name within your Blueprint
Sometimes your Blueprint might want to utilize the already existing stack.name within your Blueprint.
Runway’s CFNgin provides access to both the fully qualified stack name matching what’s shown in the CloudFormation console, in addition to the stack’s short name you have set in your YAML config.
The fully qualified name is a combination of the CFNgin namespace + the short name (what you set as name in your YAML config file).
If your CFNgin namespace is CFNginIsCool and the stack’s short name is myAwesomeEC2Instance, the fully qualified name would be CFNginIsCool-myAwesomeEC2Instance.
To use this in your Blueprint, you can get the name from context using self.context.get_fqn(self.name).
The Stack short name is the name you specified for the stack within your YAML config.
It does not include the namespace.
If your CFNgin namespace is CFNginIsCool and the stack’s short name is myAwesomeEC2Instance, the short name would be myAwesomeEC2Instance.
To use this in your Blueprint, you can get the name from the name attribute.
Example
"""Example Blueprint."""
from __future__ import annotations
from typing import TYPE_CHECKING, ClassVar, Dict
from troposphere import Tags, ec2
from runway.cfngin.blueprints.base import Blueprint
from runway.cfngin.blueprints.variables.types import CFNString
if TYPE_CHECKING:
from runway.cfngin.blueprints.type_defs import BlueprintVariableTypeDef
class ExampleBlueprint(Blueprint):
"""Example Blueprint."""
# VpcId set here to allow for Blueprint to be reused
VARIABLES: ClassVar[Dict[str, BlueprintVariableTypeDef]] = {
"VpcId": {
"type": CFNString,
"description": "The VPC to create the Security group in",
}
}
def create_template(self) -> None:
"""Create a template from the blueprint."""
# now adding a SecurityGroup resource named `SecurityGroup` to the CFN template
self.template.add_resource(
ec2.SecurityGroup(
"SecurityGroup",
# Referencing the VpcId set as the variable
VpcId=self.variables["VpcId"].ref,
# Setting the group description as the fully qualified name
GroupDescription=self.context.get_fqn(self.name),
# setting the Name tag to be the stack short name
Tags=Tags(Name=self.name),
)
)
Testing Blueprints
When writing your own Blueprint it is useful to write tests for them in order to make sure they behave the way you expect they would, especially if there is any complex logic inside.
To this end, a sub-class of the unittest.TestCase class has been provided: runway.cfngin.blueprints.testutil.BlueprintTestCase.
You use it like the regular TestCase class, but it comes with an addition assertion: assertRenderedBlueprint.
This assertion takes a Blueprint object and renders it, then compares it to an expected output, usually in tests/fixtures/blueprints.
In order to wrap the BlueprintTestCase tests in a format similar to CFNgin’s stack format, the YamlDirTestGenerator class is provided.
When subclassed in a directory, it will search for yaml files in that directory with certain structure and execute a test case for it.
Example
namespace: test
stacks:
- name: test_stack
class_path: cfngin_blueprints.s3.Buckets
variables:
var1: val1
When run from tests, this will create a template fixture file called test_stack.json containing the output from the cfngin_blueprints.s3.Buckets template.
Hooks
A hook is a python function, class, or class method that is executed before or after an action is taken for the entire config.
Only the following actions allow pre/post hooks:
- deploy
using fields
pre_deployandpost_deploy- destroy
using fields
pre_destroyandpost_destroy
- class cfngin.hook
When defining a hook in one of the supported fields, the follow fields can be used.
Lookup Support
The following fields support lookups:
- args: Optional[Dict[str, Any]] = {}
A dictionary of arguments to pass to the hook.
This field supports the use of lookups.
Important
Lookups that change the order of execution, like output, can only be used in a post hook but hooks like rxref are able to be used with either pre or post hooks.
Example
pre_deploy: - args: key: ${val}
- data_key: Optional[str] = None
If set, and the hook returns data (a dictionary or
pydantic.BaseModel), the results will be stored inCfnginContext.hook_datawith thedata_keyas its key.Example
pre_deploy: - data_key: example-key
- enabled: Optional[bool] = True
Whether to execute the hook every CFNgin run. This field provides the ability to execute a hook per environment when combined with a variable.
Example
pre_deploy: - enabled: ${enable_example_hook}
Built-in Hooks
- Hook Path
Manage a DNS validated certificate in AWS Certificate Manager.
When used in the pre_deploy or post_deploy stage this hook will create a CloudFormation stack containing a DNS validated certificate.
It will automatically create a record in Route 53 to validate the certificate and wait for the stack to complete before returning the CertificateArn as hook data.
The CloudFormation stack also outputs the ARN of the certificate as CertificateArn so that it can be referenced from other stacks.
When used in the pre_destroy or post_destroy stage this hook will delete the validation record from Route 53 then destroy the stack created during a deploy stage.
If the hook fails during a deploy stage (e.g. stack rolls back or Route 53 can’t be updated) all resources managed by this hook will be destroyed. This is done to avoid orphaning resources/record sets which would cause errors during subsequent runs. Resources effected include the CloudFormation stack it creates, ACM certificate, and Route 53 validation record.
New in version 1.6.0.
Route 53 hosted zone
authoritative for the domain the certificate is being created for
in the same AWS account as the certificate being created
- alt_names: Optional[List[str]] = []
Additional FQDNs to be included in the Subject Alternative Name extension of the ACM certificate. For example, you can add www.example.net to a certificate for which the
domainfield is www.example.com if users can reach your site by using either name.
- domain: str
The fully qualified domain name (FQDN), such as www.example.com, with which you want to secure an ACM certificate. Use an asterisk (
*) to create a wildcard certificate that protects several sites in the same domain. For example, *.example.com protects www.example.com, site.example.com, and images.example.com.
- hosted_zone_id: str
The ID of the Route 53 Hosted Zone that contains the resource record sets that you want to change. This must exist in the same account that the certificate will be created in.
- stack_name: Optional[str] = None
Provide a name for the stack used to create the certificate. If not provided, the domain is used (replacing
.with-). If the is provided in a deploy stage, its needs to be provided in the matching destroy stage.
- ttl: Optional[int] = None
The resource record cache time to live (TTL), in seconds. (default:
300)
namespace: example
cfngin_bucket: ''
sys_path: ./
pre_deploy:
acm-cert:
path: runway.cfngin.hooks.acm.Certificate
required: true
args:
domain: www.example.com
hosted_zone_id: ${rxref example-com::HostedZone}
stack:
sampleapp:
class_path: blueprints.sampleapp.BlueprintClass
variables:
cert_arn: ${rxref www-example-com::CertificateArn}
post_destroy:
acm-cert:
path: runway.cfngin.hooks.acm.Certificate
required: true
args:
domain: www.example.com
hosted_zone_id: ${rxref example-com::HostedZone}
Deprecated since version 2.5.0: Replaced by awslambda.PythonFunction.
- Hook Path
runway.cfngin.hooks.aws_lambda.upload_lambda_functions
Build Lambda payloads from user configuration and upload them to S3 using the following process:
Constructs ZIP archives containing files matching specified patterns for each function.
Uploads the result to Amazon S3
Returns a
Dictof “function name:troposphere.awslambda.Code”.
The returned value can retrieved using the hook_data Lookup or by interacting with the CfnginContext object passed to the Blueprint.
Configuration consists of some global options, and a dictionary of function specifications. In the specifications, each key indicating the name of the function (used for generating names for artifacts), and the value determines what files to include in the ZIP (see more details below).
If a requirements.txt file or Pipfile/Pipfile.lock files are found at the root of the provided path, the hook will use the appropriate method to package dependencies with your source code automatically.
If you want to explicitly use pipenv over pip, provide use_pipenv: true for the function.
Docker can be used to collect python dependencies instead of using system python to build appropriate binaries for Lambda.
This can be done by including the dockerize_pip configuration option which can have a value of true or non-linux.
Payloads are uploaded to either the cfngin_bucket or an explicitly specified bucket, with the object key containing it’s checksum to allow repeated uploads to be skipped in subsequent runs.
- bucket: Optional[str] = None
Custom bucket to upload functions to. If not provided,
cfngin_bucketwill be used.
- bucket_region: Optional[str] = None
The region in which the bucket should exist. If not provided,
cfngin_bucket_regionwill be used.
- prefix: Optional[str] = None
S3 key prefix to prepend to the uploaded zip name.
- follow_symlinks: Optional[bool] = False
Whether symlinks should be followed and included with the zip artifact.
- payload_acl: runway.cfngin.hooks.aws_lambda.PayloadAclTypeDef = private
The canned S3 object ACL to be applied to the uploaded payload.
- functions: Dict[str, Any]
Configurations of desired payloads to build. Keys correspond to function names, used to derive key names for the payload. Each value should itself be a dictionary, with the following data:
- docker_file: Optional[str] = None
Path to a local DockerFile that will be built and used for
dockerize_pip. Must provide exactly one ofdocker_file,docker_image, orruntime.
- docker_image: Optional[str] = None
Custom Docker image to use with
dockerize_pip. Must provide exactly one ofdocker_file,docker_image, orruntime.
- dockerize_pip: Optional[Union[bool, Literal['non-linux']]] = None
Whether to use Docker when restoring dependencies with pip. Can be set to
true/falseor the special stringnon-linuxwhich will only run on non Linux systems. To use this option Docker must be installed.
- exclude: Optional[Union[List[str], str]] = None
Pattern or list of patterns of files to exclude from the payload. If provided, any files that match will be ignored, regardless of whether they match an inclusion pattern.
Commonly ignored files are already excluded by default, such as
.git,.svn,__pycache__,*.pyc,.gitignore, etc.
- include: Optional[List[str], str] = None
Pattern or list of patterns of files to include in the payload. If provided, only files that match these patterns will be included in the payload.
Omitting it is equivalent to accepting all files that are not otherwise excluded.
- path: str
Base directory of the Lambda function payload content. If it not an absolute path, it will be considered relative to the directory containing the CFNgin configuration file in use.
Files in this directory will be added to the payload ZIP, according to the include and exclude patterns. If no patterns are provided, all files in this directory (respecting default exclusions) will be used.
Files are stored in the archive with path names relative to this directory. So, for example, all the files contained directly under this directory will be added to the root of the ZIP file.
- python_path: Optional[str] = None
Absolute path to a python interpreter to use for
pip/pipenvactions. If not provided, the current python interpreter will be used forpipandpipenvwill be used from the current$PATH.
- runtime: Optional[str] = None
Runtime of the AWS Lambda Function being uploaded. Used with
dockerize_pipto automatically select the appropriate Docker image to use. Must provide exactly one ofdocker_file,docker_image, orruntime.
- use_pipenv: Optional[bool] = False
Will determine if pipenv will be used to generate requirements.txt from an existing Pipfile. To use this option pipenv must be installed.
pre_deploy:
- path: runway.cfngin.hooks.aws_lambda.upload_lambda_functions
required: true
enabled: true
data_key: lambda
args:
bucket: custom-bucket
follow_symlinks: true
prefix: cloudformation-custom-resources/
payload_acl: authenticated-read
functions:
MyFunction:
path: ./lambda_functions
dockerize_pip: non-linux
use_pipenv: true
runtime: python3.9
include:
- '*.py'
- '*.txt'
exclude:
- '*.pyc'
- test/
"""Example Blueprint."""
from __future__ import annotations
from typing import cast
from troposphere.awslambda import Code, Function
from runway.cfngin.blueprints.base import Blueprint
class LambdaBlueprint(Blueprint):
"""Example Blueprint."""
def create_template(self) -> None:
"""Create a template from the blueprint."""
code = cast(Code, self.context.hook_data["lambda"]["MyFunction"])
self.template.add_resource(
Function(
"MyFunction",
Code=code,
Handler="my_function.handler",
Role="...",
Runtime="python3.9",
)
)
This hook creates deployment packages for Python Lambda Functions, uploads them to S3, and returns data about the deployment package.
The return value can be retrieved using the hook_data or by interacting with the CfnginContext object passed to the Blueprint.
To use this hook to install dependencies, it must be able to find project metadata files.
This can include Pipefile & Pipfile.lock files (pipenv), a pyproject.toml & poetry.lock files (poetry), or a requirements.txt file (pip).
The project metadata files can exist either in the source code directory (value of source_code arg) or in the same directory as the CFNgin configuration file.
If metadata files are not found, dependencies will not be included in the deployment package.
This hook will always use Docker to install/compile dependencies unless explicitly configured not to. It is recommended to always use Docker to ensure a clean and consistent build. It also ensures that binary files built during the install process are compatible with AWS Lambda.
New in version 2.5.0.
Table of Contents
Arguments that can be passed to the hook in the args field.
Note
Documentation for each field is automatically generated from class attributes in the source code. When specifying the field, exclude the class name.
- PythonHookArgs.bucket_name: str
Name of the S3 Bucket where deployment package is/will be stored. The Bucket must be in the same region the Lambda Function is being deployed in.
- PythonHookArgs.cache_dir: Optional[pathlib.Path]
Explicitly define the directory location. Must be an absolute path or it will be relative to the CFNgin module directory.
If not provided, the cache directory is
.runway/awslambda/pip_cachewithin the current working directory.
- PythonHookArgs.docker: runway.cfngin.hooks.awslambda.models.args.DockerOptions
Docker options.
- DockerOptions.disabled: bool
Explicitly disable the use of docker (default
False).If not disabled and Docker is unreachable, the hook will result in an error.
Example
args: docker: disabled: true
- DockerOptions.extra_files: List[str]
List of absolute file paths within the Docker container to copy into the deployment package.
Some Python packages require extra OS libraries (
*.so) files at runtime. These files need to be included in the deployment package for the Lambda Function to run. List the files here and the hook will handle copying them into the deployment package.The file name may end in a wildcard (
*) to accommodate.sofiles that end in an variable number (see example below).If the file does not exist, it will result in an error.
Example
args: docker: extra_files: - /usr/lib64/mysql/libmysqlclient.so.* - /usr/lib64/libxmlsec1-openssl.so
- DockerOptions.file: Optional[pathlib.Path]
Dockerfile to use to build an image for use in this process.
This,
image, orruntimemust be provided. If not provided,imagewill be used.Example
args: docker: file: Dockerfile
- DockerOptions.image: Optional[str]
Docker image to use. If the image does not exist locally, it will be pulled.
This,
file(takes precedence), orruntimemust be provided. If onlyruntimeis provided, it will be used to determine the appropriate image to use.Example
args: docker: image: public.ecr.aws/sam/build-python3.9:latest
- DockerOptions.name: Optional[str]
When providing a Dockerfile, this will be the name applied to the resulting image. It is the equivalent to
namein thename:tagsyntax of thedocker build [--tag, -t]command option.If not provided, a default image name is used.
This field is ignore unless
fileis provided.Example
args: docker: file: Dockerfile name: ${namespace}.runway.awslambda
- DockerOptions.pull: bool
Always download updates to the specified image before use. When building an image, the
FROMimage will be updated during the build process (defaultTrue).Example
args: docker: pull: false
- PythonHookArgs.extend_gitignore: List[str]
gitignore rules that should be added to the rules already defined in a
.gitignorefile in the source code directory. This can be used with or without an existing file. Files that match a gitignore rule will not be included in the deployment package..git/&.gitignorewill always be added.Important
This only applies to files in the
source_codedirectory.Example
args: extend_gitignore: - cfngin.yml - poetry.lock - poetry.toml - pyproject.toml
- PythonHookArgs.extend_pip_args: Optional[List[str]]
Additional arguments that should be passed to
pip install.Important
When providing this field, be careful not to duplicate any of the arguments passed by this hook (e.g.
--requirements,--target,--no-input). Providing duplicate arguments will result in an error.Example
args: extend_pip_args: - '--proxy' - '[user:passwd@]proxy.server:port'
- PythonHookArgs.object_prefix: Optional[str]
Prefix to add to the S3 Object key.
The object will always be prefixed with
awslambda/functions. If provided, the value will be added to the end of the static prefix (e.g.awslambda/<functions|layers>/<object_prefix>/<file name>).
- PythonHookArgs.runtime: Optional[str]
Runtime of the Lambda Function (https://docs.aws.amazon.com/lambda/latest/dg/lambda-runtimes.html).
This,
docker.file, ordocker.imagemust be provided. Ifdocker.disabled, this field is required.When provided, the runtime available on the build system (Docker container or localhost) will be checked against this value. If they do not match, an error will be raised.
If the defined or detected runtime ever changes so that it no longer matches the deployment package in S3, the deployment package in S3 will be deleted and a new one will be built and uploaded.
- PythonHookArgs.slim: bool
Automatically remove information and caches from dependencies (default
True). This is done by applying the following gitignore rules to the dependencies:**/*.dist-info***/*.py[c|d|i|o]**/*.so**/__pycache__*
- PythonHookArgs.source_code: pathlib.Path
Path to the Lambda Function source code.
Example
args: source_code: ./my/package
- PythonHookArgs.strip: bool
Whether or not to strip binary files from the dependencies (default
True). This only takes effect ifslim: true.If false, the gitignore rule
**/*.sois not used.
- PythonHookArgs.use_cache: bool
Whether to use a cache directory with pip that will persist builds (default
True).
- PythonHookArgs.use_pipenv: bool
Whether pipenv should be used if determined appropriate.
- PythonHookArgs.use_poetry: bool
Whether poetry should be used if determined appropriate.
- class runway.cfngin.hooks.awslambda.models.responses.AwsLambdaHookDeployResponse[source]
Data model for AwsLambdaHook deploy response.
When returned by the hook as
hook_data, this model is dumped to a standardDictusing the field’s aliases as thekeyin place of the attribute names. This is done so that thekeyis a direct match to a CloudFormation Property where the value should be used.- bucket_name: str
Name of the S3 Bucket where the deployment package is located. (alias
S3Bucket)
- code_sha256: str
SHA256 of the deployment package. This can be used by CloudFormation as the value of
AWS::Lambda::Version.CodeSha256. (aliasCodeSha256)
- compatible_architectures: Optional[List[str]]
A list of compatible instruction set architectures. (https://docs.aws.amazon.com/lambda/latest/dg/foundation-arch.html) (alias
CompatibleArchitectures)
- compatible_runtimes: Optional[List[str]]
A list of compatible function runtimes. Used for filtering with
ListLayersandListLayerVersions. (aliasCompatibleRuntimes)
- license: Optional[str]
The layer’s software license (alias
License). Can be any of the following:A SPDX license identifier (e.g.
MIT).The URL of a license hosted on the internet (e.g.
https://opensource.org/licenses/MIT).The full text of the license.
- object_key: str
Key (file path) of the deployment package S3 Object. (alias
S3Key)
- object_version_id: Optional[str]
The version ID of the deployment package S3 Object. This will only have a value if the S3 Bucket has versioning enabled. (alias
S3ObjectVersion)
- runtime: str
Runtime of the Lambda Function. (alias
Runtime)
FROM public.ecr.aws/sam/build-python3.9:latest
RUN yum install libxml2-devel xmlsec1-devel xmlsec1-openssl-devel libtool-ltdl-devel -y
namespace: ${namespace}
cfngin_bucket: ${cfngin_bucket}
src_path: ./
pre_deploy:
- path: runway.cfngin.hooks.awslambda.PythonFunction
data_key: awslambda.example-function-no-docker
args:
bucket_name: ${bucket_name}
docker:
disabled: true
extend_gitignore:
- "*.lock"
- '*.md'
- '*.toml'
- tests/
extend_pip_args:
- '--proxy'
- '[user:passwd@]proxy.server:port'
runtime: python3.9
slim: false
source_code: ./src/example-function
- path: runway.cfngin.hooks.awslambda.PythonFunction
data_key: awslambda.example-function
args:
bucket_name: ${bucket_name}
# docker: # example of default & inferred values
# disabled: false # default value
# image: public.ecr.aws/sam/build-python3.9:latest # inferred from runtime
# pull: true # default value
extend_gitignore:
- "*.lock"
- '*.md'
- '*.toml'
- tests/
extend_pip_args:
- '--proxy'
- '[user:passwd@]proxy.server:port'
runtime: python3.9
source_code: ./src/example-function
- path: runway.cfngin.hooks.awslambda.PythonFunction
data_key: awslambda.xmlsec
args:
bucket_name: ${bucket_name}
docker:
extra_files:
- /usr/lib64/libltdl.so.*
- /usr/lib64/libxml2.so.*
- /usr/lib64/libxmlsec1-openssl.so
- /usr/lib64/libxmlsec1.so.*
- /usr/lib64/libxslt.so.*
file: ./Dockerfile
pull: false
extend_gitignore:
- "*.lock"
- '*.md'
- '*.toml'
- tests/
source_code: ./src/xmlsec-function
strip: false
stacks:
- name: example-stack
class_path: blueprints.ExampleBlueprint
parameters:
XmlCodeSha256: ${awslambda.CodeSha256 awslambda.xmlsec}
XmlRuntime: ${awslambda.Runtime awslambda.xmlsec}
XmlS3Bucket: ${awslambda.S3Bucket awslambda.xmlsec}
XmlS3Key: ${awslambda.S3Key awslambda.xmlsec}
...
This hook creates deployment packages for Python Lambda Layers, uploads them to S3, and returns data about the deployment package.
The return value can be retrieved using the hook_data or by interacting with the CfnginContext object passed to the Blueprint.
To use this hook to install dependencies, it must be able to find project metadata files.
This can include Pipefile & Pipfile.lock files (pipenv), a pyproject.toml & poetry.lock files (poetry), or a requirements.txt file (pip).
The project metadata files can exist either in the source code directory (value of source_code arg) or in the same directory as the CFNgin configuration file.
If metadata files are not found, dependencies will not be included in the deployment package.
This hook will always use Docker to install/compile dependencies unless explicitly configured not to. It is recommended to always use Docker to ensure a clean and consistent build. It also ensures that binary files built during the install process are compatible with AWS Lambda.
New in version 2.5.0.
Table of Contents
Arguments that can be passed to the hook in the args field.
Documentation for each field is automatically generated from class attributes in the source code. When specifying the field, exclude the class name.
- PythonHookArgs.bucket_name: str
Name of the S3 Bucket where deployment package is/will be stored. The Bucket must be in the same region the Lambda Function is being deployed in.
- PythonHookArgs.cache_dir: Optional[pathlib.Path]
Explicitly define the directory location. Must be an absolute path or it will be relative to the CFNgin module directory.
If not provided, the cache directory is
.runway/awslambda/pip_cachewithin the current working directory.
- PythonHookArgs.compatible_architectures: Optional[List[str]]
A list of compatible instruction set architectures. (https://docs.aws.amazon.com/lambda/latest/dg/foundation-arch.html)
Only used by Lambda Layers.
Example
args: compatible_architectures: - x86_64 - arm64
- PythonHookArgs.compatible_runtimes: Optional[List[str]]
A list of compatible function runtimes. When provided, the
runtimebeing used to build the deployment package must be included in the list or an error will be raised.Only used by Lambda Layers.
Example
args: compatible_runtimes: - python3.9 - python3.10
- PythonHookArgs.docker: runway.cfngin.hooks.awslambda.models.args.DockerOptions
Docker options.
- DockerOptions.disabled: bool
Explicitly disable the use of docker (default
False).If not disabled and Docker is unreachable, the hook will result in an error.
Example
args: docker: disabled: true
- DockerOptions.extra_files: List[str]
List of absolute file paths within the Docker container to copy into the deployment package.
Some Python packages require extra OS libraries (
*.so) files at runtime. These files need to be included in the deployment package for the Lambda Function to run. List the files here and the hook will handle copying them into the deployment package.The file name may end in a wildcard (
*) to accommodate.sofiles that end in an variable number (see example below).If the file does not exist, it will result in an error.
Example
args: docker: extra_files: - /usr/lib64/mysql/libmysqlclient.so.* - /usr/lib64/libxmlsec1-openssl.so
- DockerOptions.file: Optional[pathlib.Path]
Dockerfile to use to build an image for use in this process.
This,
image, orruntimemust be provided. If not provided,imagewill be used.Example
args: docker: file: Dockerfile
- DockerOptions.image: Optional[str]
Docker image to use. If the image does not exist locally, it will be pulled.
This,
file(takes precedence), orruntimemust be provided. If onlyruntimeis provided, it will be used to determine the appropriate image to use.Example
args: docker: image: public.ecr.aws/sam/build-python3.9:latest
- DockerOptions.name: Optional[str]
When providing a Dockerfile, this will be the name applied to the resulting image. It is the equivalent to
namein thename:tagsyntax of thedocker build [--tag, -t]command option.If not provided, a default image name is used.
This field is ignore unless
fileis provided.Example
args: docker: file: Dockerfile name: ${namespace}.runway.awslambda
- DockerOptions.pull: bool
Always download updates to the specified image before use. When building an image, the
FROMimage will be updated during the build process (defaultTrue).Example
args: docker: pull: false
- PythonHookArgs.extend_gitignore: List[str]
gitignore rules that should be added to the rules already defined in a
.gitignorefile in the source code directory. This can be used with or without an existing file. Files that match a gitignore rule will not be included in the deployment package..git/&.gitignorewill always be added.Important
This only applies to files in the
source_codedirectory.Example
args: extend_gitignore: - cfngin.yml - poetry.lock - poetry.toml - pyproject.toml
- PythonHookArgs.extend_pip_args: Optional[List[str]]
Additional arguments that should be passed to
pip install.Important
When providing this field, be careful not to duplicate any of the arguments passed by this hook (e.g.
--requirements,--target,--no-input). Providing duplicate arguments will result in an error.Example
args: extend_pip_args: - '--proxy' - '[user:passwd@]proxy.server:port'
- PythonHookArgs.license: Optional[str]
The layer’s software license. Can be any of the following:
A SPDX license identifier (e.g.
Apache-2.0).The URL of a license hosted on the internet (e.g.
https://opensource.org/licenses/Apache-2.0).The full text of the license.
Only used by Lambda Layers.
Example
args: license: Apache-2.0
- PythonHookArgs.object_prefix: Optional[str]
Prefix to add to the S3 Object key.
The object will always be prefixed with
awslambda/functions. If provided, the value will be added to the end of the static prefix (e.g.awslambda/<functions|layers>/<object_prefix>/<file name>).
- PythonHookArgs.runtime: Optional[str]
Runtime of the Lambda Function (https://docs.aws.amazon.com/lambda/latest/dg/lambda-runtimes.html).
This,
docker.file, ordocker.imagemust be provided. Ifdocker.disabled, this field is required.When provided, the runtime available on the build system (Docker container or localhost) will be checked against this value. If they do not match, an error will be raised.
If the defined or detected runtime ever changes so that it no longer matches the deployment package in S3, the deployment package in S3 will be deleted and a new one will be built and uploaded.
- PythonHookArgs.slim: bool
Automatically remove information and caches from dependencies (default
True). This is done by applying the following gitignore rules to the dependencies:**/*.dist-info***/*.py[c|d|i|o]**/*.so**/__pycache__*
- PythonHookArgs.source_code: pathlib.Path
Path to the Lambda Function source code.
Example
args: source_code: ./my/package
- PythonHookArgs.strip: bool
Whether or not to strip binary files from the dependencies (default
True). This only takes effect ifslim: true.If false, the gitignore rule
**/*.sois not used.
- PythonHookArgs.use_cache: bool
Whether to use a cache directory with pip that will persist builds (default
True).
- PythonHookArgs.use_pipenv: bool
Whether pipenv should be used if determined appropriate.
- PythonHookArgs.use_poetry: bool
Whether poetry should be used if determined appropriate.
- class runway.cfngin.hooks.awslambda.models.responses.AwsLambdaHookDeployResponse[source]
Data model for AwsLambdaHook deploy response.
When returned by the hook as
hook_data, this model is dumped to a standardDictusing the field’s aliases as thekeyin place of the attribute names. This is done so that thekeyis a direct match to a CloudFormation Property where the value should be used.- bucket_name: str
Name of the S3 Bucket where the deployment package is located. (alias
S3Bucket)
- code_sha256: str
SHA256 of the deployment package. This can be used by CloudFormation as the value of
AWS::Lambda::Version.CodeSha256. (aliasCodeSha256)
- compatible_architectures: Optional[List[str]]
A list of compatible instruction set architectures. (https://docs.aws.amazon.com/lambda/latest/dg/foundation-arch.html) (alias
CompatibleArchitectures)
- compatible_runtimes: Optional[List[str]]
A list of compatible function runtimes. Used for filtering with
ListLayersandListLayerVersions. (aliasCompatibleRuntimes)
- license: Optional[str]
The layer’s software license (alias
License). Can be any of the following:A SPDX license identifier (e.g.
MIT).The URL of a license hosted on the internet (e.g.
https://opensource.org/licenses/MIT).The full text of the license.
- object_key: str
Key (file path) of the deployment package S3 Object. (alias
S3Key)
- object_version_id: Optional[str]
The version ID of the deployment package S3 Object. This will only have a value if the S3 Bucket has versioning enabled. (alias
S3ObjectVersion)
- runtime: str
Runtime of the Lambda Function. (alias
Runtime)
FROM public.ecr.aws/sam/build-python3.9:latest
RUN yum install libxml2-devel xmlsec1-devel xmlsec1-openssl-devel libtool-ltdl-devel -y
namespace: ${namespace}
cfngin_bucket: ${cfngin_bucket}
src_path: ./
pre_deploy:
- path: runway.cfngin.hooks.awslambda.PythonLayer
data_key: awslambda.example-function-no-docker
args:
bucket_name: ${bucket_name}
compatible_runtimes:
- python3.9
- python3.10
docker:
disabled: true
extend_gitignore:
- "*.lock"
- '*.md'
- '*.toml'
- tests/
extend_pip_args:
- '--proxy'
- '[user:passwd@]proxy.server:port'
runtime: python3.9
slim: false
source_code: ./src/example-function
- path: runway.cfngin.hooks.awslambda.PythonLayer
data_key: awslambda.example-function
args:
bucket_name: ${bucket_name}
# docker: # example of default & inferred values
# disabled: false # default value
# image: public.ecr.aws/sam/build-python3.9:latest # inferred from runtime
# pull: true # default value
extend_gitignore:
- "*.lock"
- '*.md'
- '*.toml'
- tests/
extend_pip_args:
- '--proxy'
- '[user:passwd@]proxy.server:port'
runtime: python3.9
source_code: ./src/example-function
- path: runway.cfngin.hooks.awslambda.PythonLayer
data_key: awslambda.xmlsec
args:
bucket_name: ${bucket_name}
docker:
extra_files:
- /usr/lib64/libltdl.so.*
- /usr/lib64/libxml2.so.*
- /usr/lib64/libxmlsec1-openssl.so
- /usr/lib64/libxmlsec1.so.*
- /usr/lib64/libxslt.so.*
file: ./Dockerfile
pull: false
extend_gitignore:
- "*.lock"
- '*.md'
- '*.toml'
- tests/
source_code: ./src/xmlsec-function
strip: false
stacks:
- name: example-stack
class_path: blueprints.ExampleBlueprint
parameters:
XmlCompatibleRuntimes: ${awslambda.CompatibleRuntimes awslambda.xmlsec}
XmlS3Bucket: ${awslambda.S3Bucket awslambda.xmlsec}
XmlS3Key: ${awslambda.S3Key awslambda.xmlsec}
...
- Hook Path
runway.cfngin.hooks.staticsite.build_staticsite.build
Build static site. Used by the Static Site module type.
Changed in version 2.0.0: Moved from runway.hooks to runway.cfngin.hooks.
See Static Site module documentation for details.
- Hook Path
runway.cfngin.hooks.cleanup_s3.purge_bucket
Delete objects in a Bucket.
Primarily used as a pre_destroy hook before deleting an S3 bucket.
Changed in version 2.0.0: Moved from runway.hooks to runway.cfngin.hooks.
- bucket_name: str
Name of the S3 bucket.
- Hook Path
runway.cfngin.hooks.cleanup_ssm.delete_param
Delete SSM parameter. Primarily used when an SSM parameter is created by a hook rather than CloudFormation.
Changed in version 2.0.0: Moved from runway.hooks to runway.cfngin.hooks.
- parameter_name: str
Name of an SSM parameter.
- Hook Path
runway.cfngin.hooks.command.run_command
Run a shell custom command as a hook.
- capture: Optional[bool] = False
If enabled, capture the command’s stdout and stderr, and return them in the hook result.
- interactive: Optional[bool] = False
If enabled, allow the command to interact with stdin. Otherwise, stdin will be set to the null device.
- ignore_status: Optional[bool] = False
Don’t fail the hook if the command returns a non-zero status.
- quiet: Optional[bool] = False
Redirect the command’s stdout and stderr to the null device, silencing all output. Should not be enabled if
captureis also enabled.
- stdin: Optional[str] = None
String to send to the stdin of the command. Implicitly disables
interactive.
- env: Optional[Dict[str, str]] = None
Dictionary of environment variable overrides for the command context. Will be merged with the current environment.
- **kwargs
Any other arguments will be forwarded to the
subprocess.Popenfunction. Interesting ones include:cwdandshell.
pre_deploy:
- path: runway.cfngin.hooks.command.run_command
required: true
enabled: true
data_key: copy_env
args:
command: ['cp', 'environment.template', 'environment']
- path: runway.cfngin.hooks.command.run_command
required: true
enabled: true
data_key: get_git_commit
args:
command: ['git', 'rev-parse', 'HEAD']
cwd: ./my-git-repo
capture: true
- path: runway.cfngin.hooks.command.run_command
args:
command: '`cd $PROJECT_DIR/project; npm install`'
env:
PROJECT_DIR: ./my-project
shell: true
- Hook Path
runway.cfngin.hooks.docker.image.build
Docker image build hook.
Replicates the functionality of the docker image build CLI command.
New in version 1.18.0.
- docker: Optional[Dict[str, Any]] = {}
Options for
docker image build.- custom_context: bool = False
Optional if providing a path to a zip file.
- extra_hosts: Optional[Dict[str, str]] = None
Extra hosts to add to
/etc/hostsin the building containers. Defined as a mapping of hostname to IP address.
- forcerm: bool = False
Always remove intermediate containers, even after unsuccessful builds.
- isolation: Optional[str] = None
Isolation technology used during build.
- network_mode: Optional[str] = None
Network mode for the run commands during build.
- nocache: bool = False
Don’t use cache when set to
True.
- platform: Optional[str] = None
Set platform if server is multi-platform capable. Uses format
os[/arch[/variant]].
- pull: bool = False
Download any updates to the FROM image in the Dockerfile.
- rm: bool = True
Remove intermediate containers.
- squash: bool = False
Squash the resulting image layers into a single layer.
- tag: Optional[str] = None
Optional name and tag to apply to the base image when it is built.
- target: Optional[str] = None
Name of the build-stage to build in a multi-stage Dockerfile.
- timeout: Optional[int] = None
HTTP timeout.
- use_config_proxy: bool = False
If
Trueand if the docker client configuration file (~/.docker/config.jsonby default) contains a proxy configuration, the corresponding environment variables will be set in the container being built.
- dockerfile: Optional[str] = "./Dockerfile"
Path within the build context to the Dockerfile.
- ecr_repo: Optional[Dict[str, Optional[str]]] = None
Information describing an ECR repository. This is used to construct the repository URL. If providing a value for this field, do not provide a value for
repo.If using a private registry, only
repo_nameis required. If using a public registry,repo_nameandregistry_alias.- account_id: Optional[str] = None
AWS account ID that owns the registry being logged into. If not provided, it will be acquired automatically if needed.
- aws_region: Optional[str] = None
AWS region where the registry is located. If not provided, it will be acquired automatically if needed.
- registry_alias: Optional[str] = None
If it is a public repository, provide the alias.
- repo_name: str
The name of the repository.
- path: Optional[str]
Path to the directory containing the Dockerfile.
- repo: Optional[str] = None
URI of a non Docker Hub repository where the image will be stored. If providing one of the other repo values, leave this value empty.
- tags: Optional[List[str]] = ["latest"]
List of tags to apply to the image.
- type
- description
The value of item
imagein the returned object is set to theDockerImagethat was just created.
The returned object is accessible with the hook_data Lookup under the data_key of docker (do not specify a data_key for the hook, this is handled automatically).
Important
Each execution of this hook overwrites any previous values stored in this attribute. It is advices to consume the resulting image object after it has been built, if it will be consumed by a later hook/stack.
Example
pre_deploy:
- path: runway.cfngin.hooks.docker.login
args:
ecr: true
password: ${ecr login-password}
- path: runway.cfngin.hooks.docker.image.build
args:
ecr_repo:
repo_name: ${cfn ${namespace}-test-ecr.Repository}
tags:
- latest
- python3.9
- path: runway.cfngin.hooks.docker.image.push
args:
image: ${hook_data docker.image}
- Hook Path
runway.cfngin.hooks.docker.image.push
Docker image push hook.
Replicates the functionality of the docker image push CLI command.
New in version 1.18.0.
- ecr_repo: Optional[Dict[str, Optional[str]]] = None
Information describing an ECR repository. This is used to construct the repository URL. If providing a value for this field, do not provide a value for
repoorimage.If using a private registry, only
repo_nameis required. If using a public registry,repo_nameandregistry_alias.- account_id: Optional[str] = None
AWS account ID that owns the registry being logged into. If not provided, it will be acquired automatically if needed.
- aws_region: Optional[str] = None
AWS region where the registry is located. If not provided, it will be acquired automatically if needed.
- registry_alias: Optional[str] = None
If it is a public repository, provide the alias.
- repo_name: str
The name of the repository.
- image: Optional[DockerImage] = None
A
DockerImageobject. This can be retrieved fromhook_datafor a preceding docker.image.build using the hook_data Lookup.If providing a value for this field, do not provide a value for
ecr_repoorrepo.
- repo: Optional[str] = None
URI of a non Docker Hub repository where the image will be stored. If providing one of the other repo values or
image, leave this value empty.
- tags: Optional[List[str]] = ["latest"]
List of tags to push.
pre_deploy:
- path: runway.cfngin.hooks.docker.login
args:
ecr: true
password: ${ecr login-password}
- path: runway.cfngin.hooks.docker.image.build
args:
ecr_repo:
repo_name: ${cfn ${namespace}-test-ecr.Repository}
tags:
- latest
- python3.9
- path: runway.cfngin.hooks.docker.image.push
args:
image: ${hook_data docker.image}
stacks:
ecr-lambda-function:
class_path: blueprints.EcrFunction
variables:
ImageUri: ${hook_data docker.image.uri.latest}
- Hook Path
runway.cfngin.hooks.docker.image.remove
Docker image remove hook.
Replicates the functionality of the docker image remove CLI command.
New in version 1.18.0.
- ecr_repo: Optional[Dict[str, Optional[str]]] = None
Information describing an ECR repository. This is used to construct the repository URL. If providing a value for this field, do not provide a value for
repoorimage.If using a private registry, only
repo_nameis required. If using a public registry,repo_nameandregistry_alias.- account_id: Optional[str] = None
AWS account ID that owns the registry being logged into. If not provided, it will be acquired automatically if needed.
- aws_region: Optional[str] = None
AWS region where the registry is located. If not provided, it will be acquired automatically if needed.
- registry_alias: Optional[str] = None
If it is a public repository, provide the alias.
- repo_name: str
The name of the repository.
- force: Optional[bool] = False
Whether to force the removal of the image.
- image: Optional[DockerImage] = None
A
DockerImageobject. This can be retrieved fromhook_datafor a preceding docker.image.build using the hook_data Lookup.If providing a value for this field, do not provide a value for
ecr_repoorrepo.
- noprune: Optional[bool] = False
Whether to delete untagged parents.
- repo: Optional[str] = None
URI of a non Docker Hub repository where the image will be stored. If providing one of the other repo values or
image, leave this value empty.
- tags: Optional[List[str]] = ["latest"]
List of tags to remove.
pre_deploy:
- path: runway.cfngin.hooks.docker.login
args:
ecr: true
password: ${ecr login-password}
- path: runway.cfngin.hooks.docker.image.build
args:
ecr_repo:
repo_name: ${cfn ${namespace}-test-ecr.Repository}
tags:
- latest
- python3.9
- path: runway.cfngin.hooks.docker.image.push
args:
image: ${hook_data docker.image}
tags:
- latest
- python3.9
stacks:
...
post_deploy:
- path: runway.cfngin.hooks.docker.image.remove
args:
image: ${hook_data docker.image}
tags:
- latest
- python3.9
- Hook Path
runway.cfngin.hooks.docker.login
Docker login hook.
Replicates the functionality of the docker login CLI command.
New in version 1.18.0.
- dockercfg_path: Optional[str] = None
Use a custom path for the Docker config file (
$HOME/.docker/config.jsonif present, otherwise$HOME/.dockercfg).
- ecr: Optional[Dict[str, Optional[str]]] = None
Information describing an ECR repository. This is used to construct the repository URL. If providing a value for this field, do not provide a value for
repoorimage.If using a private registry, only
repo_nameis required. If using a public registry,repo_nameandregistry_alias.- account_id: Optional[str] = None
AWS account ID that owns the registry being logged into. If not provided, it will be acquired automatically if needed.
- alias: Optional[str] = None
If it is a public registry, provide the alias.
- aws_region: Optional[str] = None
AWS region where the registry is located. If not provided, it will be acquired automatically if needed.
- email: Optional[str] = None
The email for the registry account.
- password: str
The plaintext password for the registry account.
- registry: Optional[str] = None
URL to the registry (e.g.
https://index.docker.io/v1/).If providing a value for this field, do not provide a value for
ecr.
- username: Optional[str] = None
The registry username. Defaults to
AWSif supplyingecr.
pre_deploy:
- path: runway.cfngin.hooks.docker.login
args:
ecr: true
password: ${ecr login-password}
- Hook Path
runway.cfngin.hooks.ecr.purge_repository
Purge all images from an ECR repository.
New in version 1.18.0.
- repository_name: str
The name of the ECR repository to purge.
pre_destroy:
- path: runway.cfngin.hooks.ecr.purge_repository
args:
repository_name: example-repo
- Hook Path
runway.cfngin.hooks.ecs.create_clusters
Create ECS clusters.
- clusters: List[str]
Names of clusters to create.
- Hook Path
runway.cfngin.hooks.iam.create_ecs_service_role
Create ecsServiceRole IAM role.
- role_name: Optional[str] = "ecsServiceRole"
Name of the role to create.
- Hook Path
runway.cfngin.hooks.iam.ensure_server_cert_exists
Ensure server certificate exists.
- cert_name: str
Name of the certificate that should exist.
- prompt: bool = True
Whether to prompt to upload a certificate if one does not exist.
- Hook Path
runway.cfngin.hooks.keypair.ensure_keypair_exists
Ensure a specific keypair exists within AWS. If the key doesn’t exist, upload it.
- keypair: str
Name of the key pair to create
- public_key_path: Optional[str] = None
Path to a public key file to be imported instead of generating a new key. Incompatible with the SSM options, as the private key will not be available for storing.
- ssm_key_id: Optional[str] = None
ID of a KMS key to encrypt the SSM parameter with. If omitted, the default key will be used.
- ssm_parameter_name: Optional[str] = None
Path to an SSM store parameter to receive the generated private key, instead of importing it or storing it locally.
- Hook Path
runway.cfngin.hooks.route53.create_domain
Create a domain within route53.
- domain: str
Domain name for the Route 53 hosted zone to be created.
Create, update, and delete a SecureString SSM parameter.
A SecureString parameter is any sensitive data that needs to be stored and referenced in a secure manner. If you have data that you don’t want users to alter or reference in plaintext, such as passwords or license keys, create those parameters using the SecureString datatype.
When used in the pre_deploy or post_deploy stage this hook will create or update an SSM parameter.
When used in the pre_destroy or post_destroy stage this hook will delete an SSM parameter.
New in version 2.2.0.
- allowed_pattern: Optional[str] = None
A regular expression used to validate the parameter value.
- data_type: Optional[Literal['aws:ec2:image', 'text']] = None
The data type for a String parameter. Supported data types include plain text and Amazon Machine Image IDs.
- description: Optional[str] = None
Information about the parameter.
- force: bool = False
Skip checking the current value of the parameter, just put it. Can be used alongside overwrite to always update a parameter.
- key_id: Optional[str] = None
The KMS Key ID that you want to use to encrypt a parameter. Either the default AWS Key Management Service (AWS KMS) key automatically assigned to your AWS account or a custom key.
- name: str
The fully qualified name of the parameter that you want to add to the system.
- overwrite: bool = True
Allow overwriting an existing parameter. If this is set to
Falseand the parameter already exists, the parameter will not be updated and a warning will be logged.
- policies: Optional[Union[List[Dict[str, Any]], str]] = None
One or more policies to apply to a parameter. This field takes a JSON array.
- tags: Optional[Union[Dict[str, str], List[TagTypeDef]]] = None
Tags to be applied to the parameter.
- tier: Literal['Advanced', 'Intelligent-Tiering', 'Standard'] = "Standard"
The parameter tier to assign to a parameter.
- value: Optional[str] = None
The parameter value that you want to add to the system. Standard parameters have a value limit of 4 KB. Advanced parameters have a value limit of 8 KB.
If the value of this field is falsy, the parameter will not be created or updated.
If the value of this field matches what is already in SSM Parameter Store, it will not be updated unless force is
True.
pre_deploy: &hooks
- path: runway.cfngin.hooks.ssm.parameter.SecureString
args:
name: /example/foo
value: bar
- path: runway.cfngin.hooks.ssm.parameter.SecureString
args:
name: /example/parameter1
description: This is an example.
tags:
tag-key: tag-value
tier: Advanced
value: ${value_may_be_none}
- path: runway.cfngin.hooks.ssm.parameter.SecureString
args:
name: /example/parameter2
policies:
- Type: Expiration
Version: 1.0
Attributes:
Timestamp: 2018-12-02T21:34:33.000Z
tags:
- Key: tag-key
Value: tag-value
value: ${something_else}
post_destroy: *hooks
- Hook Path
runway.cfngin.hooks.staticsite.upload_staticsite.sync
Sync static website to S3 bucket. Used by the Static Site module type.
Changed in version 2.0.0: Moved from runway.hooks to runway.cfngin.hooks.
See Static Site module documentation for details.
Writing A Custom Hook
A custom hook must be in an executable, importable python package or standalone file.
The hook must be importable using your current sys.path.
This takes into account the sys_path defined in the config file as well as any paths of package_sources.
When executed, the hook will have various keyword arguments passed to it.
The keyword arguments that will always be passed to the hook are context (CfnginContext) and provider (Provider).
Anything defined in the args field will also be passed to hook as a keyword argument.
For this reason, it is recommended to use an unpack operator (**kwargs) in addition to the keyword arguments the hook requires to ensure future compatibility and account for misconfigurations.
The hook must return True or a truthy object if it was successful.
It must return False or a falsy object if it failed.
This signifies to CFNgin whether or not to halt execution if the hook is required.
If a Dict, MutableMap, or pydantic.BaseModel is returned, it can be accessed by subsequent hooks, lookups, or Blueprints from the context object.
It will be stored as context.hook_data[data_key] where data_key is the value set in the hook definition.
If data_key is not provided or the type of the returned data is not a Dict, MutableMap, or pydantic.BaseModel, it will not be added to the context object.
Important
When using a pydantic.root_validator() or pydantic.validator() allow_reuse=True must be passed to the decorator.
This is because of how hooks are loaded/re-loaded for each usage.
Failure to do so will result in an error if the hook is used more than once.
If using boto3 in a hook, use context.get_session() instead of creating a new session to ensure the correct credentials are used.
"""context.get_session() example."""
from __future__ import annotations
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from runway.context import CfnginContext
def do_something(context: CfnginContext, **_kwargs: Any) -> None:
"""Do something."""
s3_client = context.get_session().client("s3")
"""My hook."""
from typing import Dict, Optional
def do_something(
*, is_failure: bool = True, name: str = "Kevin", **_kwargs: str
) -> Optional[Dict[str, str]]:
"""Do something."""
if is_failure:
return None
return {"result": f"You are not a failure {name}."}
namespace: example
sys_path: ./
pre_deploy:
- path: hooks.my_hook.do_something
args:
is_failure: false
Hook classes must implement the interface detailed by the CfnginHookProtocol Protocol.
This can be done implicitly or explicitly (by creating a subclass of CfnginHookProtocol).
As shown in this example, HookArgsBaseModel or it’s parent class BaseModel can be used to create self validating and sanitizing data models.
These can then be used to parse the values provided in the args field to ensure they match what is expected.
"""My hook."""
import logging
from typing import TYPE_CHECKING, Any, Dict, Optional
from runway.utils import BaseModel
from runway.cfngin.hooks.protocols import CfnginHookProtocol
if TYPE_CHECKING:
from ...context import CfnginContext
LOGGER = logging.getLogger(__name__)
class MyClassArgs(BaseModel):
"""Arguments for MyClass hook.
Attributes:
is_failure: Force the hook to fail if true.
name: Name used in the response.
"""
is_failure: bool = False
name: str
class MyClass(CfnginHookProtocol):
"""My class does a thing.
Keyword Args:
is_failure (bool): Force the hook to fail if true.
name (str): Name used in the response.
Returns:
Dict[str, str]: Response message is stored in ``result``.
Example:
.. code-block:: yaml
pre_deploy:
- path: hooks.my_hook.MyClass
args:
is_failure: False
name: Karen
"""
args: MyClassArgs
def __init__(self, context: CfnginContext, **kwargs: Any) -> None:
"""Instantiate class.
Args:
context: Context instance. (passed in by CFNgin)
provider: Provider instance. (passed in by CFNgin)
"""
kwargs.setdefault("tags", {})
self.args = self.ARGS_PARSER.parse_obj(kwargs)
self.args.tags.update(context.tags)
self.context = context
def post_deploy(self) -> Optional[Dict[str, str]]:
"""Run during the **post_deploy** stage."""
if self.args["is_failure"]:
return None
return {"result": f"You are not a failure {self.args['name']}."}
def post_destroy(self) -> None:
"""Run during the **post_destroy** stage."""
LOGGER.error("post_destroy is not supported by this hook")
def pre_deploy(self) -> None:
"""Run during the **pre_deploy** stage."""
LOGGER.error("pre_deploy is not supported by this hook")
def pre_destroy(self) -> None:
"""Run during the **pre_destroy** stage."""
LOGGER.error("pre_destroy is not supported by this hook")
namespace: example
sys_path: ./
pre_deploy:
- path: hooks.my_hook.MyClass
args:
is_failure: False
name: Karen
Lookups
Important
Runway lookups and CFNgin lookups are not interchangeable. While they do share a similar base class and syntax, they exist in two different registries. Runway config files can’t use CFNgin lookups just as the CFNgin config cannot use Runway lookups.
Runway’s CFNgin provides the ability to dynamically replace values in the config via a concept called lookups. A lookup is meant to take a value and convert it by calling out to another service or system.
A lookup is denoted in the config with the ${<lookup type> <lookup input>} syntax.
Lookups are only resolved within Variables. They can be nested in any part of a YAML data structure and within another lookup itself.
Note
If a lookup has a non-string return value, it can be the only lookup within a field.
e.g. if custom returns a list, this would raise an exception:
Variable: ${custom something}, ${output otherStack.Output}
This is valid:
Variable: ${custom something}
For example, given the following:
stacks:
- name: sg
class_path: some.stack.blueprint.Blueprint
variables:
Roles:
- ${output otherStack.IAMRole}
Values:
Env:
Custom: ${custom ${output otherStack.Output}}
DBUrl: postgres://${output dbStack.User}@${output dbStack.HostName}
The Blueprint would have access to the following resolved variables dictionary:
{
"Roles": ["other-stack-iam-role"],
"Values": {
"Env": {
"Custom": "custom-output",
"DBUrl": "postgres://user@hostname",
},
},
}
Built-in Lookups
- Query Syntax
[<region>@]<argument>:<argument-value> <argument>:<argument-value>,<argument-value>
The ami lookup is meant to search for the most recent AMI created that matches the given filters.
Any other arguments specified but not listed below are sent as filters to the AWS API.
For example, architecture:x86_64 would add a filter.
- region: Optional[str]
AWS region to search (e.g.
us-east-1). Defaults to the current region.
- owners: Union[List[str], str]
At least one owner must be specified in the query (e.g.
amazon,self, or an AWS account ID). Multiple owners can be provided by using a comma to delimitate the list.
- name_regex: str
Regex pattern for the name of the AMI (e.g.
my-ubuntu-server-[0-9]+).
- executable_users: Optional[str]
amazon,self, or an AWS account ID.
# Grabs the most recently created AMI that is owned by either this account,
# amazon, or the account id 888888888888 that has a name that matches
# the regex "server[0-9]+" and has "i386" as its architecture.
# Note: The region is optional, and defaults to the current CFNgin region
ImageId: ${ami [<region>@]owners:self,888888888888,amazon name_regex:server[0-9]+ architecture:i386}
- Query Syntax
<hook.data_key>
Dedicated lookup for use with AwsLambdaHook based hooks.
To use this hook, there must be a
AwsLambdaHook based hook defined
in the pre_deploy section of the CFNgin configuration file.
This hook must also define a data_key that is unique within
the CFNgin configuration file (it can be reused in other CFNgin configuration files).
The data_key is then passed to the lookup as it’s input/query.
This allows the lookup to function during a runway plan.
An AwsLambdaHookDeployResponse object is returned by this lookup.
It is recommended to only use this lookup when passing the value into a Blueprint or hook as further processing will be required.
New in version 2.5.0.
namespace: example
cfngin_bucket: ''
sys_path: ./
pre_deploy:
- path: runway.cfngin.hooks.awslambda.PythonFunction
data_key: example-function-01
args:
...
- path: runway.cfngin.hooks.awslambda.PythonFunction
data_key: example-function-02
args:
...
stacks:
- name: example-stack-01
class_path: blueprints.FooStack
variables:
code_metadata: ${awslambda example-function-01}
...
- name: example-stack-02
class_path: blueprints.BarStack
variables:
code_metadata: ${awslambda example-function-02}
...
- Query Syntax
<hook.data_key>
Dedicated lookup for use with AwsLambdaHook based hooks.
To use this hook, there must be a
AwsLambdaHook based hook defined
in the pre_deploy section of the CFNgin configuration file.
This hook must also define a data_key that is unique within
the CFNgin configuration file (it can be reused in other CFNgin configuration files).
The data_key is then passed to the lookup as it’s input/query.
This allows the lookup to function during a runway plan.
A troposphere.awslambda.Code object is returned by this lookup.
It is recommended to only use this lookup when passing the value into a Blueprint or hook as further processing will be required.
However, it can be passed directly in the Code keyword argument of troposphere.awslambda.Function.
New in version 2.5.0.
namespace: example
cfngin_bucket: ''
sys_path: ./
pre_deploy:
- path: runway.cfngin.hooks.awslambda.PythonFunction
data_key: example-function-01
args:
...
- path: runway.cfngin.hooks.awslambda.PythonFunction
data_key: example-function-02
args:
...
stacks:
- name: example-stack-01
class_path: blueprints.FooStack
variables:
code_object: ${awslambda.Code example-function-01}
...
- name: example-stack-02
class_path: blueprints.BarStack
variables:
code_object: ${awslambda.Code example-function-02}
...
- Query Syntax
<hook.data_key>
Dedicated lookup for use with AwsLambdaHook based hooks.
To use this hook, there must be a
AwsLambdaHook based hook defined
in the pre_deploy section of the CFNgin configuration file.
This hook must also define a data_key that is unique within
the CFNgin configuration file (it can be reused in other CFNgin configuration files).
The data_key is then passed to the lookup as it’s input/query.
This allows the lookup to function during a runway plan.
A string is returned by this lookup. The returned value can be passed directly to AWS::Lambda::Version.CodeSha256.
New in version 2.5.0.
namespace: example
cfngin_bucket: ''
sys_path: ./
pre_deploy:
- path: runway.cfngin.hooks.awslambda.PythonFunction
data_key: example-function-01
args:
...
- path: runway.cfngin.hooks.awslambda.PythonFunction
data_key: example-function-02
args:
...
stacks:
- name: example-stack-01
class_path: blueprints.FooStack
variables:
CodeSha256: ${awslambda.CodeSha256 example-function-01}
...
- name: example-stack-02
template_path: ./templates/bar-stack.yml
variables:
CodeSha256: ${awslambda.CodeSha256 example-function-02}
...
- Query Syntax
<hook.data_key>
Dedicated lookup for use with AwsLambdaHook based hooks.
To use this hook, there must be a
AwsLambdaHook based hook defined
in the pre_deploy section of the CFNgin configuration file.
This hook must also define a data_key that is unique within
the CFNgin configuration file (it can be reused in other CFNgin configuration files).
The data_key is then passed to the lookup as it’s input/query.
This allows the lookup to function during a runway plan.
A list of strings or None is returned by this lookup.
The returned value can be passed directly to AWS::Lambda::LayerVersion.CompatibleArchitectures.
New in version 2.5.0.
This lookup only supports the transform argument which can be used to turn the list of strings into a comma delimited list.
namespace: example
cfngin_bucket: ''
sys_path: ./
pre_deploy:
- path: runway.cfngin.hooks.awslambda.PythonLayer
data_key: example-layer-01
args:
...
- path: runway.cfngin.hooks.awslambda.PythonLayer
data_key: example-layer-02
args:
...
stacks:
- name: example-stack-01
class_path: blueprints.FooStack
variables:
CompatibleArchitectures: ${awslambda.CompatibleArchitectures example-layer-01}
...
- name: example-stack-02
template_path: ./templates/bar-stack.yml
variables:
CompatibleArchitectures: ${awslambda.CompatibleArchitectures example-layer-02::transform=str}
...
- Query Syntax
<hook.data_key>
Dedicated lookup for use with AwsLambdaHook based hooks.
To use this hook, there must be a
AwsLambdaHook based hook defined
in the pre_deploy section of the CFNgin configuration file.
This hook must also define a data_key that is unique within
the CFNgin configuration file (it can be reused in other CFNgin configuration files).
The data_key is then passed to the lookup as it’s input/query.
This allows the lookup to function during a runway plan.
A list of strings or None is returned by this lookup.
The returned value can be passed directly to AWS::Lambda::LayerVersion.CompatibleRuntimes.
New in version 2.5.0.
This lookup only supports the transform argument which can be used to turn the list of strings into a comma delimited list.
namespace: example
cfngin_bucket: ''
sys_path: ./
pre_deploy:
- path: runway.cfngin.hooks.awslambda.PythonLayer
data_key: example-layer-01
args:
...
- path: runway.cfngin.hooks.awslambda.PythonLayer
data_key: example-layer-02
args:
...
stacks:
- name: example-stack-01
class_path: blueprints.FooStack
variables:
CompatibleRuntimes: ${awslambda.CompatibleRuntimes example-layer-01}
...
- name: example-stack-02
template_path: ./templates/bar-stack.yml
variables:
CompatibleRuntimes: ${awslambda.CompatibleRuntimes example-layer-02::transform=str}
...
- Query Syntax
<hook.data_key>
Dedicated lookup for use with AwsLambdaHook based hooks.
To use this hook, there must be a
AwsLambdaHook based hook defined
in the pre_deploy section of the CFNgin configuration file.
This hook must also define a data_key that is unique within
the CFNgin configuration file (it can be reused in other CFNgin configuration files).
The data_key is then passed to the lookup as it’s input/query.
This allows the lookup to function during a runway plan.
A troposphere.awslambda.Content object is returned by this lookup.
It is recommended to only use this lookup when passing the value into a Blueprint or hook as further processing will be required.
However, it can be passed directly in the Content keyword argument of troposphere.awslambda.LayerVersion.
New in version 2.5.0.
namespace: example
cfngin_bucket: ''
sys_path: ./
pre_deploy:
- path: runway.cfngin.hooks.awslambda.PythonLayer
data_key: example-layer-01
args:
...
- path: runway.cfngin.hooks.awslambda.PythonLayer
data_key: example-layer-02
args:
...
stacks:
- name: example-stack-01
class_path: blueprints.FooStack
variables:
layer_content: ${awslambda.Content example-layer-01}
...
- name: example-stack-02
class_path: blueprints.BarStack
variables:
layer_content: ${awslambda.Content example-layer-02}
...
- Query Syntax
<hook.data_key>
Dedicated lookup for use with AwsLambdaHook based hooks.
To use this hook, there must be a
AwsLambdaHook based hook defined
in the pre_deploy section of the CFNgin configuration file.
This hook must also define a data_key that is unique within
the CFNgin configuration file (it can be reused in other CFNgin configuration files).
The data_key is then passed to the lookup as it’s input/query.
This allows the lookup to function during a runway plan.
A string or None is returned by this lookup.
The returned value can be passed directly to AWS::Lambda::LayerVersion.License.
New in version 2.5.0.
namespace: example
cfngin_bucket: ''
sys_path: ./
pre_deploy:
- path: runway.cfngin.hooks.awslambda.PythonLayer
data_key: example-layer-01
args:
...
- path: runway.cfngin.hooks.awslambda.PythonLayer
data_key: example-layer-02
args:
...
stacks:
- name: example-stack-01
class_path: blueprints.FooStack
variables:
License: ${awslambda.License example-layer-01}
...
- name: example-stack-02
template_path: ./templates/bar-stack.yml
variables:
License: ${awslambda.License example-layer-02}
...
- Query Syntax
<hook.data_key>
Dedicated lookup for use with AwsLambdaHook based hooks.
To use this hook, there must be a
AwsLambdaHook based hook defined
in the pre_deploy section of the CFNgin configuration file.
This hook must also define a data_key that is unique within
the CFNgin configuration file (it can be reused in other CFNgin configuration files).
The data_key is then passed to the lookup as it’s input/query.
This allows the lookup to function during a runway plan.
A string is returned by this lookup.
The returned value can be passed directly to AWS::Lambda::Function.Runtime.
While not necessary, using this hook to fill in Runtime ensures compatibility with the deployment package and removes the need for duplicating configuration values.
New in version 2.5.0.
namespace: example
cfngin_bucket: ''
sys_path: ./
pre_deploy:
- path: runway.cfngin.hooks.awslambda.PythonFunction
data_key: example-function-01
args:
...
- path: runway.cfngin.hooks.awslambda.PythonFunction
data_key: example-function-02
args:
...
stacks:
- name: example-stack-01
class_path: blueprints.FooStack
variables:
Runtime: ${awslambda.Runtime example-function-01}
...
- name: example-stack-02
template_path: ./templates/bar-stack.yml
variables:
Runtime: ${awslambda.Runtime example-function-02}
...
- Query Syntax
<hook.data_key>
Dedicated lookup for use with AwsLambdaHook based hooks.
To use this hook, there must be a
AwsLambdaHook based hook defined
in the pre_deploy section of the CFNgin configuration file.
This hook must also define a data_key that is unique within
the CFNgin configuration file (it can be reused in other CFNgin configuration files).
The data_key is then passed to the lookup as it’s input/query.
This allows the lookup to function during a runway plan.
A string is returned by this lookup. The returned value can be passed directly to AWS::Lambda::Function.Code.S3Bucket or AWS::Lambda::LayerVersion.Content.S3Bucket.
New in version 2.5.0.
namespace: example
cfngin_bucket: ''
sys_path: ./
pre_deploy:
- path: runway.cfngin.hooks.awslambda.PythonFunction
data_key: example-function-01
args:
...
- path: runway.cfngin.hooks.awslambda.PythonFunction
data_key: example-function-02
args:
...
stacks:
- name: example-stack-01
class_path: blueprints.FooStack
variables:
S3Bucket: ${awslambda.S3Bucket example-function-01}
...
- name: example-stack-02
template_path: ./templates/bar-stack.yml
variables:
S3Bucket: ${awslambda.S3Bucket example-function-02}
...
- Query Syntax
<hook.data_key>
Dedicated lookup for use with AwsLambdaHook based hooks.
To use this hook, there must be a
AwsLambdaHook based hook defined
in the pre_deploy section of the CFNgin configuration file.
This hook must also define a data_key that is unique within
the CFNgin configuration file (it can be reused in other CFNgin configuration files).
The data_key is then passed to the lookup as it’s input/query.
This allows the lookup to function during a runway plan.
A string is returned by this lookup. The returned value can be passed directly to AWS::Lambda::Function.Code.S3Key or AWS::Lambda::LayerVersion.Content.S3Key.
New in version 2.5.0.
namespace: example
cfngin_bucket: ''
sys_path: ./
pre_deploy:
- path: runway.cfngin.hooks.awslambda.PythonFunction
data_key: example-function-01
args:
...
- path: runway.cfngin.hooks.awslambda.PythonFunction
data_key: example-function-02
args:
...
stacks:
- name: example-stack-01
class_path: blueprints.FooStack
variables:
S3Key: ${awslambda.S3Key example-function-01}
...
- name: example-stack-02
template_path: ./templates/bar-stack.yml
variables:
S3Key: ${awslambda.S3Key example-function-02}
...
- Query Syntax
<hook.data_key>
Dedicated lookup for use with AwsLambdaHook based hooks.
To use this hook, there must be a
AwsLambdaHook based hook defined
in the pre_deploy section of the CFNgin configuration file.
This hook must also define a data_key that is unique within
the CFNgin configuration file (it can be reused in other CFNgin configuration files).
The data_key is then passed to the lookup as it’s input/query.
This allows the lookup to function during a runway plan.
A string is returned by this lookup. The returned value can be passed directly to AWS::Lambda::Function.Code.S3ObjectVersion or AWS::Lambda::LayerVersion.Content.S3ObjectVersion.
New in version 2.5.0.
namespace: example
cfngin_bucket: ''
sys_path: ./
pre_deploy:
- path: runway.cfngin.hooks.awslambda.PythonFunction
data_key: example-function-01
args:
...
- path: runway.cfngin.hooks.awslambda.PythonFunction
data_key: example-function-02
args:
...
stacks:
- name: example-stack-01
class_path: blueprints.FooStack
variables:
S3ObjectVersion: ${awslambda.S3ObjectVersion example-function-01}
...
- name: example-stack-02
template_path: ./templates/bar-stack.yml
variables:
S3ObjectVersion: ${awslambda.S3ObjectVersion example-function-02}
...
Important
The Stack must exist in CloudFormation before the config using this Lookup begins processing to successfully get a value.
This means that it must have been deployed using another Runway module, deployed from a config that is run before the one using it, deployed manually, or deployed in the same config using required/required_by to specify a dependency between the Stacks.
- Query Syntax
<stack-name>.<output-name>[::<arg>=<arg-val>, ...]
Retrieve a value from CloudFormation Stack Outputs.
When specifying the output name, be sure to use the Logical ID of the output; not the Export.Name.
If the Lookup is unable to find a CloudFormation Stack Output matching the provided query, the default value is returned or an exception is raised to show why the value could be be resolved (e.g. Stack does not exist or output does not exist on the Stack).
New in version 1.11.0.
See also
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/outputs-section-structure.html
This Lookup supports all Common Lookup Arguments.
namespace: example
stacks:
- ...
variables:
VpcId: ${cfn ${namespace}-vpc.Id}
Given the above config file, the lookup will get the value of the Output named Id from Stack example-vpc.
- Query Syntax
<env_var>::<default value>
The default lookup type will check if a value exists for the variable in the environment file, then fall back to a default defined in the CFNgin config if the environment file doesn’t contain the variable. This allows defaults to be set at the config file level, while granting the user the ability to override that value per environment.
Note
The default lookup only supports checking if a variable is defined in an environment file. It does not support other embedded lookups to see if they exist. Only checking variables in the environment file are supported. If you attempt to have the default lookup perform any other lookup that fails, CFNgin will throw an exception for that lookup and will exit before it gets a chance to fall back to the default in your config.
Groups: ${default app_security_groups::sg-12345,sg-67890}
If app_security_groups is defined in the environment file, its defined value will be returned. Otherwise, sg-12345,sg-67890 will be the returned value.
- Query Syntax
<region>:<table-name>@<partition-key>:<value>.<attribute>
The dynamodb lookup type retrieves a value from a DynamoDb table.
As an example, if you have a Dynamo Table named TestTable and it has an Item with a Primary Partition key called TestKey and a value named BucketName, you can look it up by using CFNgin.
The lookup key in this case is TestVal
# We can reference that dynamo value
BucketName: ${dynamodb us-east-1:TestTable@TestKey:TestVal.BucketName}
# Which would resolve to:
BucketName: test-bucket
You can lookup other data types by putting the data type in the lookup.
Valid values are S (String), N (Number), M (Map), L (List).
ServerCount: ${dynamodb us-east-1:TestTable@TestKey:TestVal.ServerCount[N]}
This would return an int value, rather than a string
You can lookup values inside of a map.
ServerCount: ${dynamodb us-east-1:TestTable@TestKey:TestVal.ServerInfo[M].ServerCount[N]}
Retrieve a value from AWS Elastic Container Registry (ECR).
This Lookup only supports very specific queries.
New in version 1.18.0.
Get a password to login to ECR registry.
The returned value can be passed to the login command of the container client of your preference, such as the CFNgin docker.login. After you have authenticated to an Amazon ECR registry with this Lookup, you can use the client to push and pull images from that registry as long as your IAM principal has access to do so until the token expires. The authorization token is valid for 12 hours.
This Lookup does not support any arguments.
pre_deploy:
- path: runway.cfngin.hooks.docker.login
args:
password: ${ecr login-password}
...
- Query Syntax
<variable-name>[::<arg>=<arg-val>, ...]
Retrieve a value from an environment variable.
The value is retrieved from a copy of the current environment variables that is saved to the context object.
These environment variables are manipulated at runtime by Runway to fill in additional values such as DEPLOY_ENVIRONMENT and AWS_REGION to match the current execution.
If the Lookup is unable to find an environment variable matching the provided query, the default value is returned or a ValueError is raised if a default value was not provided.
New in version 2.7.0.
This Lookup supports all Common Lookup Arguments but, the following have limited or no effect:
region
stacks:
- ...
variables:
Foo: ${env bar::default=foobar}
Deprecated since version 2.7.0: Replaced by env
- Query Syntax
<variable-name>
The envvar lookup type retrieves a value from a variable in the shell’s environment.
# Set an environment variable in the current shell.
$ export DATABASE_USER=root
# In the CFNgin config we could reference the value:
DBUser: ${envvar DATABASE_USER}
# Which would resolve to:
DBUser: root
You can also get the variable name from a file, by using the file:// prefix in the lookup, like so:
DBUser: ${envvar file://dbuser_file.txt}
- Query Syntax
<supported-codec>:<data>
The file lookup type allows the loading of arbitrary data from files.
The lookup additionally supports using a codec to parse and/or manipulate the file contents prior to returning it.
The parameterized-b64 codec is particularly useful to allow the interpolation of CloudFormation parameters in a UserData attribute of an instance or launch configuration.
If the file can be read locally, the <data> portion of the query should look something like file://./path/to/file.
The file:// prefix tells CFNgin that it needs to open the file located at the provide path and read it’s contents before continuing.
For a relative path, it will be relative to the current working directory (usually the root of the CFNgin module being processed).
If <data> is not prefixed with file://, it will be treated as the contents of the file.
This enables lookups to be chained together to retrieve data and still take advantage of a codec to further parse and/or manipulate it as needed.
For example, the value of an SSM Parameter can be parsed as json-parameterized before it is returned by the lookup with the following ${file json-parameterized:${ssm /parameter/name}}.
plain - Load the contents of the file untouched. This is the only codec that should be used with raw Cloudformation templates (the other codecs are intended for blueprints).
base64 - Encode the plain text file at the given path with base64 prior to returning it.
parameterized - The same as plain, but additionally supports referencing CloudFormation parameters to create userdata that’s supplemented with information from the template, as is commonly needed in EC2 UserData. For example, given a template parameter of BucketName, the file could contain the following text:
#!/bin/sh aws s3 sync s3://{{BucketName}}/somepath /somepath
and then you could use something like this in the YAML config file:
UserData: ${file parameterized:file://path/to/file}
resulting in the UserData parameter being defined as:
{ "Fn::Join" : [ "", [ "#!/bin/sh\naws s3 sync s3://", { "Ref" : "BucketName" }, "/somepath /somepath" ] ] }
parameterized-b64 - The same as parameterized, with the results additionally wrapped in
{ "Fn::Base64": ... }, which can be used as EC2 UserData.When using parameterized-b64 for UserData, you should use a parameter defined as such.
from troposphere import AWSHelperFn "UserData": { "type": AWSHelperFn, "description": "Instance user data", "default": Ref("AWS::NoValue") }
Then set UserData in a LaunchConfiguration or Instance to
self.variables["UserData"]. Note that we use AWSHelperFn as the type because the parameterized-b64 codec returns either a Base64 or a GenericHelperFn troposphere object.json - Decode the file as JSON and return the resulting object.
json-parameterized - Same as
json, but applying templating rules fromparameterizedto every object value. Note that object keys are not modified.Example (an external PolicyDocument):
{ "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": [ "some:Action" ], "Resource": "{{MyResource}}" } ] }
yaml - Decode the file as YAML and return the resulting object.
yaml-parameterized - Same as
json-parameterized, but using YAML.Version: 2012-10-17 Statement: - Effect: Allow Action: - "some:Action" Resource: "{{MyResource}}"
# We've written a file to /some/path:
$ echo "hello there" > /some/path
# In CFNgin we would reference the contents of this file with the following
conf_key: ${file plain:file://some/path}
# The above would resolve to
conf_key: hello there
# Or, if we used wanted a base64 encoded copy of the file data
conf_key: ${file base64:file://some/path}
# The above would resolve to
conf_key: aGVsbG8gdGhlcmUK
- Query Syntax
<hook.data_key>[::<arg>=<arg-val>, ...]
When using hooks, you can have the hook store results in the CfnginContext.hook_data dictionary on the context by setting data_key in the hook config.
This lookup lets you look up values in that dictionary. A good example of this is when you use the aws_lambda.upload_lambda_functions to upload AWS Lambda code, then need to pass that code object as the Code variable in a Blueprint.
Changed in version 2.0.0: Support for the syntax deprecated in 1.5.0 has been removed.
Changed in version 1.5.0: The <hook_name>::<key> syntax was deprecated with support being added for the key.nested_key syntax for accessing data within a dictionary.
This Lookup supports all Common Lookup Arguments but, the following have limited or no effect:
region
# If you set the ``data_key`` config on the aws_lambda hook to be "myfunction"
# and you name the function package "TheCode" you can get the troposphere
# awslambda.Code object with:
Code: ${hook_data myfunction.TheCode}
# If you need to pass the code location as individual strings for use in a
# CloudFormation template instead of a Blueprint, you can do so like this:
Bucket: ${hook_data myfunction.TheCode::load=troposphere, get=S3Bucket}
Key: ${hook_data myfunction.TheCode::load=troposphere, get=S3Key}
- Query Syntax
<encrypted-blob>[::region=<region>, ...]
The kms lookup type decrypts its input value.
As an example, if you have a database and it has a parameter called DBPassword that you don’t want to store in plain text in your config (maybe because you want to check it into your version control system to share with the team), you could instead en
crypt the value using kms.
Changed in version 2.7.0: The [<region>@]<encrypted-blob> syntax is deprecated to comply with Runway’s lookup syntax.
This Lookup supports all Common Lookup Arguments but, the following have limited or no effect:
default
We use can use the aws cli to get the encrypted value for the string “PASSWORD” using the master key called ‘myKey’ in us-east-1.
$ aws --region us-east-1 kms encrypt --key-id alias/myKey \
--plaintext "PASSWORD" --output text --query CiphertextBlob
CiD6bC8t2Y<...encrypted blob...>
namespace: example
stacks:
- ...
variables:
# With CFNgin we would reference the encrypted value like:
DBPassword: ${kms CiD6bC8t2Y<...encrypted blob...>::region=us-east-1}
# The above would resolve to:
DBPassword: PASSWORD
This requires that the credentials used by CFNgin have access to the master key used to encrypt the value.
It is also possible to store the encrypted blob in a file (useful if the value is large) using the file:// prefix, ie:
namespace: example
stacks:
- ...
variables:
DockerConfig: ${kms file://dockercfg}
Note
Lookups resolve the path specified with file:// relative to the location of the config file, not the current working directory.
- Query Syntax
<relative-stack-name>.<output-name>[::<arg>=<arg-val>, ...]
The output lookup retrieves an Output from the given Stack name within the current namespace.
CFNgin treats output lookups differently than other lookups by auto adding the referenced stack in the lookup as a requirement to the stack whose variable the output value is being passed to.
Changed in version 2.7.0: The <relative-stack-name>::<output-name> syntax is deprecated to comply with Runway’s lookup syntax.
This Lookup supports all Common Lookup Arguments but, the following have limited or no effect:
region
You can specify an output lookup with the following syntax:
namespace: example
stacks:
- ...
variables:
ConfVariable: ${output stack-name.OutputName}
- Query Syntax
<desired-length>
Generate a random string of the given length.
New in version 2.2.0.
- digits: bool = True
When generating the random string, the string may contain digits (
[0-9]). If the string can contain digits, it will always contain at least one.
- lowercase: bool = True
When generating the random string, the string may contain lowercase letters (
[a-z]). If the string can contain lowercase letters, it will always contain at least one.
- punctuation: bool = False
When generating the random string, the string may contain ASCII punctuation (
[!"#$%&'()*+,-./:;<=>?@[\]^_`{|}~]). If the string can contain ASCII punctuation, it will always contain at least one.
- uppercase: bool = True
When generating the random string, the string may contain uppercase letters (
[A-Z]). If the string can contain uppercase letters, it will always contain at least one.
This Lookup supports all Common Lookup Arguments but, the following have limited or no effect:
default
get
indent
load
region
This example shows the use of this lookup to create an SSM parameter that will retain value generated during the first deployment. Even through subsequent deployments generate a new value that is passed to the hook, the hook does not overwrite the value of an existing parameter.
pre_deploy: &hooks
- path: runway.cfngin.hooks.ssm.parameter.SecureString
args:
name: /${namespace}/password
overwrite: false
value: ${random.string 12::punctuation=true}
post_destroy: *hooks
- Query Syntax
<relative-stack-name>.<output-name>[::<arg>=<arg-val>, ...]
The rxref lookup type is very similar to the cfn lookup type.
Where the cfn type assumes you provided a fully qualified stack name, rxref, like the output expands and retrieves the output from the given Stack name within the current namespace, even if not defined in the CFNgin config you provided it.
Because there is no requirement to keep all stacks defined within the same CFNgin YAML config, you might need the ability to read outputs from other Stacks deployed by CFNgin into your same account under the same namespace.
rxref gives you that ability.
This is useful if you want to break up very large configs into smaller groupings.
Also, unlike the output type, rxref doesn’t impact Stack requirements.
Changed in version 2.7.0: The <relative-stack-name>::<output-name> syntax is deprecated to comply with Runway’s lookup syntax.
This Lookup supports all Common Lookup Arguments.
namespace: namespace
stacks:
- ...
variables:
ConfVariable0: ${rxref my-stack.SomeOutput}
# both of these lookups are functionally equivalent
ConfVariable1: ${cfn namespace-my-stack.SomeOutput}
Although possible, it is not recommended to use rxref for stacks defined within the same CFNgin YAML config.
Doing so would require the use of required_by or requires.
- Query Syntax
<parameter>[::<arg>=<arg-val>, ...]
Retrieve a value from SSM Parameter Store.
If the Lookup is unable to find an SSM Parameter matching the provided query, the default value is returned or ParameterNotFound is raised if a default value is not provided.
Parameters of type SecureString are automatically decrypted.
Parameters of type StringList are returned as a list.
New in version 1.5.0.
This Lookup supports all Common Lookup Arguments.
stacks:
- ...
variables:
Example: ${ssm /example/secret}
Deprecated since version 1.11.0: Replaced by cfn
- Query Syntax
<fully-qualified-stack-name>::<output-name>
The xref lookup type is very similar to the output type, the difference being that xref resolves output values from stacks that aren’t contained within the current CFNgin namespace, but are existing Stacks containing outputs within the same region on the AWS account you are deploying into.
xref allows you to lookup these outputs from the Stacks already in your account by specifying the stacks fully qualified name in the CloudFormation console.
Where the output type will take a Stack name and use the current context to expand the fully qualified stack name based on the namespace, xref skips this expansion because it assumes you’ve provided it with the fully qualified stack name already.
This allows you to reference output values from any CloudFormation Stack in the same region.
Also, unlike the output type, xref doesn’t impact stack requirements.
ConfVariable: ${xref fully-qualified-stack::SomeOutput}
Writing A Custom Lookup
A custom lookup may be registered within the config.
It custom lookup must be in an executable, importable python package or standalone file.
The lookup must be importable using your current sys.path.
This takes into account the sys_path defined in the config file as well as any paths of package_sources.
The lookup must be a subclass of LookupHandler with a @classmethod of handle with a similar signature to what is provided in the example below.
The subclass must override the TYPE_NAME class variable with a name that will be used to register the lookup.
There must be only one lookup per file.
The lookup must return a string if being used for a CloudFormation parameter.
If using boto3 in a lookup, use context.get_session() instead of creating a new session to ensure the correct credentials are used.
Important
When using a pydantic.root_validator() or pydantic.validator() in a lookup allow_reuse=True must be passed to the decorator.
This is because of how lookups are loaded/re-loaded when they are registered.
Failure to do so will result in an error if the lookup is registered more than once.
Example
"""Example lookup."""
from __future__ import annotations
from typing import TYPE_CHECKING, Any, Final, Literal, Optional, Union
from runway.cfngin.utils import read_value_from_path
from runway.lookups.handlers.base import LookupHandler
if TYPE_CHECKING:
from runway.cfngin.providers.aws.default import Provider
from runway.context import CfnginContext, RunwayContext
class MylookupLookup(LookupHandler):
"""My lookup."""
TYPE_NAME: Final[Literal["mylookup"]] = "mylookup"
"""Name that the Lookup is registered as."""
@classmethod
def handle(
cls,
value: str,
context: Union[CfnginContext, RunwayContext],
*_args: Any,
provider: Optional[Provider] = None,
**_kwargs: Any
) -> str:
"""Do something.
Args:
value: Value to resolve.
context: The current context object.
provider: CFNgin AWS provider.
"""
query, args = cls.parse(read_value_from_path(value))
# example of using get_session for a boto3 session
s3_client = context.get_session().client("s3")
return "something"
Persistent Graph
Each time Runway’s CFNgin is run, it creates a dependency graph of stacks.
This is used to determine the order in which to execute them.
This graph can be persisted between runs to track the removal of stacks from the config file.
When a stack is present in the persistent graph but not in the graph constructed from the config file, CFNgin will delete the Stack from CloudFormation.
This takes effect when running either the deploy command or destroy command.
To enable persistent graph, define the persistent_graph_key field as a unique value that will be used to construct the path to the persistent graph object in S3.
This object is stored in the cfngin_bucket which is also used for CloudFormation templates.
The fully qualified path to the object will look like the below.
s3://${cfngin_bucket}/${namespace}/persistent_graphs/${namespace}/${persistent_graph_key}.json
Note
It is recommended to enable versioning on the cfngin_bucket when using persistent graph to have a backup version in the event something unintended happens.
A warning will be logged if this is not enabled.
If CFNgin creates a cfngin_bucket for you when persistent graph is enabled, it will be created with versioning enabled.
Important
When choosing a value for persistent_graph_key, it is vital to ensure the value is unique for the namespace being used.
If the key is a duplicate, Stacks that are not intended to be destroyed will be destroyed.
When executing an action that will be modifying the persistent graph (deploy or destroy), the S3 object is “locked”. The lock is a tag applied to the object at the start of one of these actions. The tag-key is cfngin_lock_code and the tag-value is UUID generated each time a config is processed.
To lock a persistent graph object, the tag must not be present on the object. For CFNgin to act on the graph (modify or unlock) the value of the tag must match the UUID of the current CFNgin session. If the object is locked or the code does not match, an error will be raised and no action will be taken. This prevents two parties from acting on the same persistent graph object concurrently which would create a race condition.
Note
A persistent graph object can be unlocked manually by removing the cfngin_lock_code tag from it. This should be done with caution as it will cause any active sessions to raise an error.
Example
namespace: example
cfngin_bucket: cfngin-bucket
persistent_graph_key: my_graph # .json - will be appended if not provided
stacks:
- name: first_stack:
...
- name: new_stack:
...
{
"first_stack": [],
"removed_stack": [
"first_stack"
]
}
Given the above config file and persistent graph, when running runway deploy, the following will occur.
The
{"Key": "cfngin_lock_code", "Value": "123456"}tag is applied to s3://cfngin-bucket/persistent_graphs/example/my_graph.json to lock it to the current session.removed_stack is deleted from CloudFormation and deleted from the persistent graph object in S3.
first_stack is updated in CloudFormation and updated in the persistent graph object in S3 (incase dependencies change).
new_stack is created in CloudFormation and added to the persistent graph object in S3.
The
{"Key": "cfngin_lock_code", "Value": "123456"}tag is removed from s3://cfngin-bucket/persistent_graphs/example/my_graph.json to unlock it for use in other sessions.
Remote Sources
The package_sources field can be used to define additional locations to include when processing a configuration file.
The locations can either be a local file path or a network accessible location.
By defining these additional sources you are able to extend your $PATH to make more resources accessible or even merge multiple configuration files into the current configuration file.
- class cfngin.package_sources
There are three different types of package sources - git repository, local, and AWS S3.
- git: Optional[List[cfngin.package_source.git]] = []
A list of git repositories to include when processing the configuration file.
See Git Repository for detailed information.
package_sources: git: ...
- local: Optional[List[cfngin.package_source.local]] = []
A list of additional local directories to include when processing the configuration file.
See Local for detailed information.
package_sources: local: ...
- s3: Optional[List[cfngin.package_source.s3]] = []
A list of AWS S3 objects to include when processing the configuration file.
See AWS S3 for detailed information.
package_sources: s3: ...
Contents
Git Repository
- class cfngin.package_source.git
Package source located in a git repository.
Cloned repositories are cached locally between runs. The cache location is defined by
cfngin.config.cfngin_cache_dir.- branch: Optional[str] = None
Name of a branch to checkout after cloning the git repository.
Only one of
branch,commit, ortagcan be defined.Example
package_sources: git: - branch: master
- commit: Optional[str] = None
After cloning the git repository, reset HEAD to the given commit hash.
Only one of
branch,commit, ortagcan be defined.Example
package_sources: git: - commit: 5d83f7ff1ad6527233be2c27e9f68816599b6c57
- configs: Optional[List[str]] = []
Configuration files from this source location can also be used by specifying a list of file paths.
These configuration files are merged into the current configuration file with the current file taking precedence. When using this usage pattern, it is advised to use dictionary definitions for everything that supports it to allow for granular overriding.
Example
package_sources: git: - configs: - example-01.yml - example-02.yml
- paths: Optional[List[str]] = []
A list of subdirectories within the source location that should be added to $PATH.
Example
package_sources: git: - paths: - some/directory/ - another/
Local
- class cfngin.package_source.local
Package source located on a local disk.
- configs: Optional[List[str]] = []
Configuration files from this source location can also be used by specifying a list of file paths.
These configuration files are merged into the current configuration file with the current file taking precedence. When using this usage pattern, it is advised to use dictionary definitions for everything that supports it to allow for granular overriding.
Example
package_sources: local: - configs: - example-01.yml - example-02.yml
AWS S3
- class cfngin.package_source.s3
Package source located in AWS S3.
S3 objects are cached locally between runs. The cache location is defined by
cfngin.config.cfngin_cache_dir.- configs: Optional[List[str]] = []
Configuration files from this source location can also be used by specifying a list of file paths.
These configuration files are merged into the current configuration file with the current file taking precedence. When using this usage pattern, it is advised to use dictionary definitions for everything that supports it to allow for granular overriding.
Example
package_sources: s3: - configs: - example-01.yml - example-02.yml
- key: str
Key for an S3 object within the
bucket. The object should be an archived file that can be unzipped.Example
package_sources: s3: - key: path/to/example.zip
- paths: Optional[List[str]] = []
A list of subdirectories within the source location that should be added to $PATH.
Example
package_sources: s3: - paths: - some/directory/ - another/
Templates
CloudFormation templates can be provided via Blueprints or JSON/YAML.
JSON/YAML templates are specified for stacks via the template_path config.
Contents
Jinja2 Templating
Templates with a .j2 extension will be parsed using Jinja2.
The CFNgin context and mappings objects and stack variables objects are available for use in the template:
Description: TestTemplate
Resources:
Bucket:
Type: AWS::S3::Bucket
Properties:
BucketName: {{ context.environment.foo }}-{{ variables.myparamname }}
Migrating from Stacker
Blueprints
Most components available in Stacker 1.7.0 are available in Runway’s CFNgin at the same path within runway.cfngin.
Example
# what use to be this
from stacker.blueprints.base import Blueprint
from stacker.blueprints.variables.types import CFNString
# now becomes this
from runway.cfngin.blueprints.base import Blueprint
from runway.cfngin.blueprints.variables.types import CFNString
Config Files
There are some config top-level keys that have changed when used Runway’s CFNgin. Below is a table of the Stacker key and what they have been changed to for Runway’s CFNgin
Stacker |
Runway’s CFNgin |
|---|---|
|
|
|
|
|
|
Build-in Hooks
All hooks available in Stacker 1.7.0 are available in Runway’s CFNgin at the same path within runway.cfngin.
Note
Some hooks have different args and/or altered functionality.
It is advised to review the documentation for the hook before using it.
Example Definition
pre_deploy:
- path: stacker.hooks.commands.run_command
args:
command: echo "Hello $USER!"
- path: runway.cfngin.hooks.commands.run_command
args:
command: echo "Hello $USER!"
See also
runway.cfnginCFNgin documentation
Custom Lookups
See the Custom Lookups section of the docs for detailed instructions on how lookups should be written.
Kubernetes
Kubernetes manifests can be deployed via Runway offering an ideal way to handle core infrastructure-layer (e.g. shared ConfigMaps & Service Accounts) configuration of clusters by using Kustomize overlays.
Configuration
Configuration options and parameters for Kubernetes modules.
Contents
Options
- kubectl_version: Optional[str] = None
Specify a version of Kubectl for Runway and download and use. See Version Management for more details.
Example
options: kubectl_version: 1.14.5
- overlay_path: Optional[str] = None
Specify the directory containing the kustomize overlay to use.
Example
options: overlay_path: overlays/${env DEPLOY_ENVIRONMENT}-blue
New in version 1.12.0.
Parameters
Kubernetes does not support the use of deployment.parameters/module.parameters at this time.
Directory Structure
Example directory structures for a Kubernetes module.
.
├── .gitignore
├── aws-auth-cm.k8s
│ ├── base
│ │ └── kustomization.yaml
│ └── overlays
│ └── template
│ └── kustomization.yaml
├── runway.yml
└── service-hello-world.k8s
├── README.md
├── base
│ ├── configMap.yaml
│ ├── deployment.yaml
│ ├── kustomization.yaml
│ └── service.yaml
└── overlays
├── prod
│ ├── deployment.yaml
│ └── kustomization.yaml
└── template
├── kustomization.yaml
└── map.yaml
Examples
Example uses of the Kubernetes module
Contents
CloudFormation EKS
To view an example using an EKS cluster deployed with CloudFormation, run runway gen-sample k8s-cfn-repo in any directory.
This will create a k8s-cfn-infrastructure/ directory in your current working directory containing a runway.yml file, some modules that can be deployed, and a README.md that provides instructions on how to work with the example code.
Terraform EKS
To view an example using an EKS cluster deployed with Terraform, run runway gen-sample k8s-tf-repo in any directory.
This will create a k8s-tf-infrastructure/ directory in your current working directory containing a runway.yml file, some modules that can be deployed, and a README.md that provides instructions on how to work with the example code.
Advanced Features
Advanced features and detailed information for using Kubernetes with Runway.
Setting KUBECONFIG Location
If using a non-default kubeconfig location, you can provide it using deployment.env_vars/module.env_vars for setting environment variables.
This can be set as a relative path or an absolute one.
deployments:
- modules:
- path: myk8smodule
env_vars:
KUBECONFIG:
- .kube
- ${env DEPLOY_ENVIRONMENT}
- config
This would set KUBECONFIG to <path_to_runway.yml>/.kube/$DEPLOY_ENVIRONMENT/config where $DEPLOY_ENVIRONMENT is the current Runway deploy environment.
Version Management
By specifying the version via a .kubectl-version file in your overlay directory or deployment.module_options/module.options, Runway will automatically download & use that version for the module.
This is recommended to keep a predictable experience when deploying your module.
Without a version specified, Runway will fallback to whatever kubectl it finds first in your PATH.
1.14.5
Lookups can be used to provide different versions for each deploy environment.
deployments:
- modules:
- path: sampleapp.k8s
options:
kubectl_version: ${var kubectl_version.${env DEPLOY_ENVIRONMENT}}
- module:
- sampleapp-01.k8s
- sampleapp-02.k8s
module_options:
kubectl_version: 1.14.5
Serverless Framework
The Serverless module type is deployed using the Serverless Framework. Runway uses system installed npm to install Serverless per-module. This means that Serverless must be included as a dev dependency in the package.json of the module.
Configuration
Standard Serverless Framework rules apply but, we have some added prerequisites, recommendations, and caveats.
Prerequisites
Serverless must be a dev dependency of the module (e.g.
npm install --save-dev serverless)
We strongly recommend you commit the package-lock.json that is generated after running npm install.
Options
Options specific to Serverless Framework modules.
- args: Optional[List[str]] = []
List of CLI arguments/options to pass to the Serverless Framework CLI. See Specifying Serverless CLI Arguments/Options for more details.
Example
options: args: - '--config' - sls.yml
New in version 1.4.0.
- extend_serverless_yml: Optional[Dict[str, Any]] = {}
If provided, the value of this option will be recursively merged into the modules serverless.yml file. See Extending a Serverless Configuration File for more details.
Example
options: extend_serverless_yml: custom: env: memorySize: 512
New in version 1.8.0.
- promotezip: Optional[Dict[str, str]] = {}
If provided, promote Serverless Framework generated zip files between environments from a build AWS account. See Promoting Builds Through Environments for more details.
Example
options: promotezip: bucketname: my-build-account-bucket-name
- skip_npm_ci: bool = False
Skip running
npm ciin the module directory prior to processing the module. See Disabling NPM CI for more details.Example
options: skip_npm_ci: true
serverless.yml
Refer to the Serverless Framework Documentation.
Stages
Runway’s concept of a deploy environment has a 1-to-1 mapping to Serverless’s stage.
For example, if the deploy environment is dev, Serverless will be run with --stage dev.
Each stage requires either its own variables file (even if empty for a particular stage) following a specific File Naming scheme and/or a configured environment for the module or deployment (see Runway Config File for details).
File Naming
env/STAGE-REGION.ymlconfig-STAGE-REGION.ymlenv/STAGE.ymlconfig-STAGE.ymlenv/STAGE-REGION.jsonconfig-STAGE-REGION.jsonenv/STAGE.jsonconfig-STAGE.json
Directory Structure
Example directory structures for a Serverless module.
Python Example
.
├── __init__.py
├── _gitignore
├── config-dev-us-east-1.json
├── hello_world
│ └── __init__.py
├── package.json
├── poetry.lock
├── pyproject.toml
└── serverless.yml
TypeScript Example
.
├── .gitignore
├── env
│ └── dev-us-east-1
├── jest.config.js
├── package.json
├── package-lock.json
├── serverless.yml
├── src
│ ├── helloWorld.test.ts
│ └── helloWorld.ts
├── tsconfig.json
├── tslint.json
└── webpack.config.js
Advanced Features
Advanced features and detailed information for using Serverless Framework with Runway.
Contents
Disabling NPM CI
At the start of each module execution, Runway will execute npm ci to ensure Serverless Framework is installed in the project (so Runway can execute it via npx sls).
This can be disabled (e.g. for use when the node_modules directory is pre-compiled) via the skip_npm_ci module option.
Example
deployments:
- modules:
- path: myslsproject.sls
options:
skip_npm_ci: true
Extending a Serverless Configuration File
Runway has the ability to extend the contents of a serverless.yml file using the value of the extend_serverless_yml option.
The value of this option is recursively merged into a resolved clone of the module’s Serverless configuration.
To create this resolved clone, Runway uses “serverless print” (including args) to resolve the module’s Serverless configuration file and output the contents to a temporary file.
The temporary file is deleted after each execution of Runway.
This functionality can be especially useful when used alongside remote module paths such as a module from a git repository to change values on the fly without needing to modify the source for small differences in each environment.
Example
deployments:
- modules:
- path: git::git://github.com/onicagroup/example.git//sampleapp?tag=v1.0.0
options:
extend_serverless_yml:
custom:
env:
memorySize: 512
regions:
- us-east-1
Merge Logic
The two data sources are merged by iterating over their content and combining the lowest level nodes possible.
Example
functions:
example:
handler: handler.example
runtime: python3.9
memorySize: 512
deployments:
- modules:
- path: sampleapp.sls
options:
extend_serverless_yml:
functions:
example:
memorySize: 1024
resources:
Resources:
ExampleResource:
Type: AWS::CloudFormation::WaitConditionHandle
regions:
- us-east-1
functions:
example:
handler: handler.example
runtime: python3.9
memorySize: 1024
resources:
Resources:
ExampleResource:
Type: AWS::CloudFormation::WaitConditionHandle
Promoting Builds Through Environments
Serverless build .zips can be used between environments by setting the promotezip module option and providing a bucket name in which to cache the builds.
The first time the Serverless module is deployed using this option, it will build/deploy as normal and cache the artifact on S3. On subsequent deploys, Runway will use the cached artifact (finding it by comparing the module source code).
This enables a common build account to deploy new builds in a dev/test environment, and then promote that same zip through other environments. Any of these environments can be in the same or different AWS accounts.
The CloudFormation Stack deploying the zip will be re-generated on each deployment so environment-specific values/lookups will work as normal.
Example
deployments:
- modules:
- path: myslsproject.sls
options:
promotezip:
bucketname: my-build-account-bucket-name
Specifying Serverless CLI Arguments/Options
Runway can pass custom arguments/options to the Serverless CLI by using the args option.
These will always be placed after the default arguments/options.
The value of args must be a list of arguments/options to pass to the CLI.
Each element of the argument/option should be it’s own list item (e.g. --config sls.yml would be ['--config', 'sls.yml']).
Important
Do not provide --region <region> or --stage <stage> here, these will be provided by Runway.
Runway will also provide --no-color if stdout is not a TTY.
Example
deployments:
- modules:
- path: sampleapp.sls
options:
args:
- '--config'
- sls.yml
regions:
- us-east-2
environments:
example: true
$ serverless deploy -r us-east-1 --stage example --config sls.yml
Static Site
This module type performs idempotent deployments of static websites. It combines CloudFormation stacks (for S3 buckets & CloudFront Distribution) with additional logic to build & sync the sites.
A start-to-finish example walkthrough is available in the Conduit quickstart.
Note
The CloudFront Distribution that is created by default can take a significant amount of time to spin up on initial deploy (5 to 60 minutes is not abnormal). Incorporating CloudFront with a static site is a common best practice, however, if you are working on a development project it may benefit you to add the staticsite_cf_disable parameter.
Configuration
Configuration options and parameters for static site modules. Example uses of the options and parameters can be found in the Examples section.
Contents
Options
- build_output: Optional[str] = None
Overrides default directory of top-level path setting.
Example
options: build_output: dist
- build_steps: Optional[List[str]] = []
The steps to run during the build portion of deployment.
Example
options: build_steps: - npm ci - npm run build
- extra_files: Optional[List[Dict[str, Union[str, Dict[str, Any]]]]] = []
Specifies extra files that should be uploaded to S3 after the build.
Use
extra_filesif you want to have a single build artifact that can be used in many environments. These files should be excluded from source hashing and the build system. The end result is that you have a build artifact that can be deployed in any environment and behave exactly the same.See Extra Files for more details.
Example
options: extra_files: - name: config.json # yaml or other text files are supported content: # this object will be json or yaml serialized endpoint: ${var api_endpoint.${env DEPLOY_ENVIRONMENT}} - name: config.any content_type: text/yaml # Explicit content type content: endpoint: ${var api_endpoint.${env DEPLOY_ENVIRONMENT}} - name: logo.png content_type: image/png file: logo-${env DEPLOY_ENVIRONMENT}.png # a reference to an existing file
The example above produces a file named
config.jsonwith the contents below and alogo.pngfile.{ "endpoint": "<api_endpoint value>" }
New in version 1.9.0.
- pre_build_steps: Optional[List[Dict[str, str]]] = []
Commands to be run before generating the hash of files.
Example
options: pre_build_steps: - command: npm ci cwd: ../myothermodule # directory relative to top-level path setting - command: npm run export cwd: ../myothermodule
- source_hashing: Optional[Dict[str, str]] = {}
Overrides for source hash collection and tracking
Example
options: source_hashing: enabled: true # if false, build & upload will occur on every deploy parameter: /${namespace}/myparam # defaults to <namespace>-<name/path>-hash directories: # overrides default hash directory of top-level path setting - path: ./ - path: ../common # Additional (gitignore-format) exclusions to # hashing (.gitignore files are loaded automatically) exclusions: - foo/*
Parameters
- cloudformation_service_role: Optional[str] = None
IAM Role ARN that CloudFormation will use when creating, deleting and updating the CloudFormation stack resources.
See the AWS CloudFormation service role for more information.
Example
parameters: cloudformation_service_role: arn:aws:iam::123456789012:role/name
- namespace: str
The unique namespace for the deployment.
Example
parameters: namespace: my-awesome-website-${env DEPLOY_ENVIRONMENT}
- staticsite_acmcert_arn: Optional[str] = None
The certificate arn used for any alias domains supplied. This is a requirement when supplying any custom domain.
Example
parameters: staticsite_acmcert_arn: arn:aws:acm:<region>:<account-id>:certificate/<cert>
- staticsite_aliases: Optional[str] = None
Any custom domains that should be added to the CloudFront Distribution. This should be represented as a comma delimited list of domains.
Requires staticsite_acmcert_arn.
Example
parameters: staticsite_aliases: example.com,foo.example.com
- staticsite_auth_at_edge: Optional[bool] = False
Auth@Edge make the static site private by placing it behind an authorization wall. See Auth@Edge for more details.
Example
parameters: staticsite_auth_at_edge: true
New in version 1.5.0.
- staticsite_cf_disable: Optional[bool] = False
Whether deployment of the CloudFront Distribution should be disabled.
Useful for a development site as it makes it accessible via an S3 url with a much shorter launch time. This cannot be set to
truewhen using Auth@Edge.Example
parameters: staticsite_cf_disable: false
New in version 1.5.0.
- staticsite_compress: Optional[bool] = True
Whether the CloudFront default cache behavior will automatically compress certain files.
Example
parameters: staticsite_compress: false
- staticsite_cookie_settings: Optional[Dict[str, str]] = {"idToken": "Path=/; Secure; SameSite=Lax", "accessToken": "Path=/; Secure; SameSite=Lax", "refreshToken": "Path=/; Secure; SameSite=Lax", "nonce": "Path=/; Secure; HttpOnly; Max-Age=1800; SameSite=Lax"}
The default cookie settings for retrieved tokens and generated nonce’s.
Requires staticsite_auth_at_edge.
Example
parameters: staticsite_cookie_settings: idToken: "Path=/; Secure; SameSite=Lax" accessToken: "Path=/; Secure; SameSite=Lax" refreshToken: "Path=/; Secure; SameSite=Lax" nonce: "Path=/; Secure; HttpOnly; Max-Age=1800; SameSite=Lax"
New in version 1.5.0.
- staticsite_create_user_pool: Optional[bool] = False
Whether to create a User Pool for the Auth@Edge configuration.
Requires staticsite_auth_at_edge.
Example
parameters: staticsite_create_user_pool: true
New in version 1.5.0.
- staticsite_custom_error_responses: Optional[List[Dict[str, Union[int, str]]]] = []
Define custom error responses.
Example
parameters: staticsite_custom_error_responses: - ErrorCode: 404 ResponseCode: 200 ResponsePagePath: /index.html
- staticsite_enable_cf_logging: Optional[bool] = True
Whether logging should be enabled for the CloudFront distribution.
Example
parameters: staticsite_enable_cf_logging: true
- staticsite_http_headers: Optional[Dict[str, str]] = {"Content-Security-Policy": "default-src https: 'unsafe-eval' 'unsafe-inline'; font-src 'self' 'unsafe-inline' 'unsafe-eval' data: https:; object-src 'none'; connect-src 'self' https://*.amazonaws.com https://*.amazoncognito.com", "Strict-Transport-Security": "max-age=31536000; includeSubdomains; preload", "Referrer-Policy": "same-origin", "X-XSS-Protection": "1; mode=block", "X-Frame-Options": "DENY", "X-Content-Type-Options": "nosniff"}
Headers that should be sent with each origin response.
Requires staticsite_auth_at_edge.
Note
Please note that the Content-Security-Policy is intentionally lax to allow for Single Page Application framework’s to work as expected. Review your Content Security Policy for your project and update these as need be to match.
Example
parameters: staticsite_http_headers: Content-Security-Policy: "default-src https: 'unsafe-eval' 'unsafe-inline'; font-src 'self' 'unsafe-inline' 'unsafe-eval' data: https:; object-src 'none'; connect-src 'self' https://*.amazonaws.com https://*.amazoncognito.com" Strict-Transport-Security: "max-age=31536000; includeSubdomains; preload" Referrer-Policy: "same-origin" X-XSS-Protection: "1; mode=block" X-Frame-Options: "DENY" X-Content-Type-Options: "nosniff"
New in version 1.5.0.
- staticsite_lambda_function_associations: Optional[List[Dict[str, str]]] = []
This section allows the user to deploy custom Lambda@Edge associations with their pre-build function versions. This takes precedence over staticsite_rewrite_directory_index and cannot currently be used with staticsite_auth_at_edge.
Example
parameters: staticsite_lambda_function_associations: - type: origin-request arn: arn:aws:lambda:<region>:<account-id>:function:<function>:<version>
- staticsite_non_spa: Optional[bool] = False
Whether this site is a single page application (SPA).
A custom error response directing
ErrorCode: 404to the primary/index.htmlas aResponseCode: 200is added, allowing the SPA to take over error handling. If you are not running an SPA, setting this totruewill prevent this custom error from being added. If provided, staticsite_custom_error_responses takes precedence over this setting.Requires staticsite_auth_at_edge.
Example
parameters: staticsite_non_spa: true
New in version 1.5.0.
- staticsite_oauth_scopes: Optional[List[str]] = ["phone", "email", "profile", "openid", "aws.cognito.signin.user.admin"]
Scope is a mechanism in OAuth 2.0 to limit an application’s access to a user’s account. An application can request one or more scopes. This information is then presented to the user in the consent screen and the access token issued to the application will be limited to the scopes granted.
Requires staticsite_auth_at_edge.
Example
parameters: staticsite_oauth_scopes: - phone - email - profile - openid - aws.cognito.signin.user.admin
New in version 1.5.0.
- staticsite_redirect_path_auth_refresh: Optional[str] = "/refreshauth"
The path that a user is redirected to when their authorization tokens have expired (1 hour).
Requires staticsite_auth_at_edge.
Example
parameters: staticsite_redirect_path_auth_refresh: /refreshauth
New in version 1.5.0.
- staticsite_redirect_path_sign_in: Optional[str] = "/parseauth"
The path that a user is redirected to after sign-in. This corresponds with the
parseauthLambda@Edge function which will parse the authentication details and verify the reception.Requires staticsite_auth_at_edge.
Example
parameters: staticsite_redirect_path_sign_in: /parseauth
New in version 1.5.0.
- staticsite_redirect_path_sign_out: Optional[str] = "/"
The path that a user is redirected to after sign-out. This typically should be the root of the site as the user will be asked to re-login.
Requires staticsite_auth_at_edge.
Example
parameters: staticsite_redirect_path_sign_out: /
New in version 1.5.0.
- staticsite_rewrite_directory_index: Optional[str] = None
Deploy a Lambda@Edge function designed to rewrite directory indexes, e.g. supports accessing urls such as
example.org/foo/Example
parameters: staticsite_rewrite_directory_index: index.html
- staticsite_role_boundary_arn: Optional[str] = None
Defines an IAM Managed Policy that will be set as the permissions boundary for any IAM Roles created to support the site. (e.g. when using staticsite_auth_at_edge or staticsite_rewrite_directory_index)
Example
parameters: staticsite_role_boundary_arn: arn:aws:iam::<account-id>:policy/<policy>
New in version 1.8.0.
- staticsite_sign_out_url: Optional[str] = "/signout"
The path a user should access to sign themselves out of the application.
Requires staticsite_auth_at_edge.
Example
parameters: staticsite_sign_out_url: /signout
New in version 1.5.0.
- staticsite_supported_identity_providers: Optional[str] = "COGNITO"
A comma delimited list of the User Pool client identity providers.
Requires staticsite_auth_at_edge.
Example
parameters: staticsite_supported_identity_providers: facebook,onelogin
New in version 1.5.0.
- staticsite_user_pool_arn: Optional[str] = None
The ARN of a pre-existing Cognito User Pool to use with Auth@Edge.
Requires staticsite_auth_at_edge.
Example
parameters staticsite_user_pool_arn: arn:aws:cognito-idp:<region>:<account-id>:userpool/<pool>
New in version 1.5.0.
- staticsite_additional_redirect_domains: Optional[str] = None
Additional domains (beyond the staticsite_aliases domains or the CloudFront URL if no aliases are provided) that will be authorized by the Auth@Edge UserPool AppClient. This parameter typically won’t be needed in production environments, but can be useful in development environments to allow bypassing Runway Auth@Edge.
This should be represented as a comma delimited list of domains with protocols. Requires staticsite_auth_at_edge.
Example
parameters: staticsite_additional_redirect_domains: http://localhost:3000
New in version 1.14.0.
- staticsite_web_acl: Optional[str] = None
The ARN of a web access control list (web ACL) to associate with the CloudFront Distribution.
Example
parameters: staticsite_web_acl: arn:aws:waf::<account-id>:certificate/<cert>
- staticsite_required_group: Optional[str] = None
Name of Cognito User Pool group of which users must be a member to be granted access to the site. Omit to allow all UserPool users to have access.
Requires staticsite_auth_at_edge.
Example
parameters: staticsite_required_group: AuthorizedUsers
New in version 1.5.0.
Directory Structure
Example directory structures for a ref:static site <mod-staticsite> module.
Contents
Angular SPA
.
├── runway.yml
└── sample-app
├── README.md
├── .gitignore
├── angular.json
├── browserslist
├── e2e
│ ├── protractor.conf.js
│ ├── src
│ │ ├── app.e2e-spec.ts
│ │ └── app.po.ts
│ └── tsconfig.json
├── karma.conf.js
├── package-lock.json
├── package.json
├── src
│ ├── app
│ │ ├── app-routing.module.ts
│ │ ├── app.component.css
│ │ ├── app.component.html
│ │ ├── app.component.spec.ts
│ │ ├── app.component.ts
│ │ └── app.module.ts
│ ├── assets
│ ├── environments
│ │ ├── environment.prod.ts
│ │ └── environment.ts
│ ├── favicon.ico
│ ├── index.html
│ ├── main.ts
│ ├── polyfills.ts
│ ├── styles.css
│ └── test.ts
├── tsconfig.app.json
├── tsconfig.json
├── tsconfig.spec.json
└── tslint.json
React SPA
.
├── runway.yml
└── sample-app
├── README.md
├── package.json
├── public
│ ├── favicon.ico
│ ├── index.html
│ ├── logo192.png
│ ├── logo512.png
│ ├── manifest.json
│ └── robots.txt
└── src
├── App.css
├── App.js
├── App.test.js
├── index.css
├── index.js
├── logo.svg
├── serviceWorker.js
└── setupTests.js
Examples
Example uses of the static site module
Contents
Angular SPA
To view an example deployment of an Angular single page application, run runway gen-sample static-angular in any directory.
This will create a new static-angular/ directory in your current working directory containing a runway.yml and a sample-app module that can be deployed.
Extra Files in Angular
By default, angular uses environment/environment.ts as its way to pass environment specific configurations into your application.
The downside to this is that you need to build your application for each environment and lose ability to build once and deploy everywhere.
The static site extra_files option solves this problem by moving environment configuration out of angular and into Runway.
A small change to the way the application references environment config will need to be made.
Wrap configuration access into a service that can be injected into your components.
In the new config service, make an http request to load the config. Since
extra_filesuploads the files to the static site bucket, this request should be relative to your application.Cache the config and use normal observable patterns to provide access.
export interface Config {
endpoint: string;
}
@Injectable({
providedIn: 'root'
})
export class AppConfig {
constructor(private http: HttpClient) {}
getConfig(): Observable<Config> {
return this.http.get<Config>('assets/config.json');
}
}
export class AppComponent implements OnInit {
title = 'Angular App';
constructor(private config: AppConfig) {}
ngOnInit() {
this.config.getConfig().subscribe((config) => {
this.title = config.endpoint;
});
}
}
variables:
website:
api_endpoint:
dev: https://api.dev.example.com
test: https://api.test.example.com
deployments:
- name: WebApp
modules:
- path: .
type: static
environments:
dev: true
test: true
options:
build_steps:
- npm ci
- npm run build
build_output: dist/web
extra_files:
- name: assets/config.json
content:
endpoint: ${var website.api_endpoint.${env DEPLOY_ENVIRONMENT}}
parameters:
namespace: my-app-namespace
staticsite_cf_disable: true
regions:
- us-east-1
Angular Development Workflow
While developing an Angular application, a local live environment is typically used and Runway is not.
This means that assets/config.json does not exist and your application would likely fail.
Take the following steps to get your development environment running.
Create a stub
src/assets/config.jsonthat defines all the configuration attributes. The values can be empty strings.Create a ‘dev’ config file:
src/assets/config-dev.json. Populate the configuration values with appropriate values for your local dev environment.Edit
angular.jsonAdd a
fileReplacementsoption toprojects.<app>.architect.build.options.{ "fileReplacements": [{ "replace": "src/assets/config.json", "with": "src/assets/config-dev.json" }] }
Run
npx ng serveNote
It would be a better practice to define a new ‘local’ configuration target instead of adding
fileReplacementsto the default configuration target.“build” Configuration{ "configurations": { "local": { "fileReplacements": [{ "replace": "src/assets/config.json", "with": "src/assets/config-local.json" }] } } }
“serve” Configuration{ "configurations": { "local": { "browserTarget": "<app>:build:local" } } }
$ npx ng serve --configuration=local
React SPA
To view an example deployment of a React single page application, run runway gen-sample static-react in any directory.
This will create a new static-react/ directory in your current working directory containing a runway.yml and a sample-app module that can be deployed.
Extra Files in React
React by itself is not concerned with different environments or how a developer initializes the application with different backends. This is more of a concern with other layers of your application stack, e.g. Redux. However, the concept is similar to the Angular examples.
// Use your favorite http client
import axios from 'axios';
// Make a request to load the config
axios.get('config.json').then(resp => {
return resp.data.endpoint;
})
.then(endpoint => {
// Render the react component
ReactDOM.render(<App message={endpoint} />, document.getElementById('root'));
});
Initialize the redux store with an initial config
axios.get('config.json').then(resp => {
return resp.data;
})
.then(config => {
// Create a redux store
return store(config);
})
.then(store => {
ReactDOM.render(
<Provider store={store}>
<App/>
</Provider>,
document.getElementById('root')
);
});
variables:
website:
api_endpoint:
dev: https://api.dev.example.com
test: https://api.test.example.com
deployments:
- name: WebApp
modules:
- path: .
type: static
environments:
dev: true
test: true
options:
build_output: build
build_steps:
- npm ci
- npm run build
extra_files:
- name: config.json
content:
endpoint: ${var website.api_endpoint.${env DEPLOY_ENVIRONMENT}}
parameters:
namespace: my-app-namespace
staticsite_cf_disable: true
regions:
- us-west-2
React Development Workflow
React doesn’t have an equivalent feature as Angular’s fileReplacements so this solution isn’t as flexible.
Create the file
public/config.json.Add content that matches the structure defined in
extra_filesand populate the values needed for local development.Example
{ "endpoint": "https://api.dev.example.com" }
(Optional) Add
public/config.jsonto.gitignoreNote
If you don’t want to add
public/config.jsonto.gitignore, you should configure Runways source hashing to exclude it.source_hashing: enabled: true directories: - path: ./ exclusions: - public/config.json
Run
npm run start
Advanced Features
Contents
Auth@Edge
Important
Auth@Edge static sites can only be deployed to us-east-1. This is due to the limitations of Lambda@Edge.
Auth@Edge provides the ability to make a static site private by using Cognito for authentication. The solution is inspired by similar implementations such as aws-samples/cloudfront-authorization-at-edge.
The following diagram depicts a high-level overview of this solution.
Here is how the solution works:
The viewer’s web browser is redirected to Amazon Cognito custom UI page to sign up and authenticate.
After authentication, Cognito generates and cryptographically signs a JWT then responds with a redirect containing the JWT embedded in the URL.
The viewer’s web browser extracts JWT from the URL and makes a request to private content (private/* path), adding Authorization request header with JWT.
Amazon CloudFront routes the request to the nearest AWS edge location. The CloudFront distribution’s private behavior is configured to launch a Lambda@Edge function on ViewerRequest event.
Lambda@Edge decodes the JWT and checks if the user belongs to the correct Cognito User Pool. It also verifies the cryptographic signature using the public RSA key for Cognito User Pool. Crypto verification ensures that JWT was created by the trusted party.
After passing all of the verification steps, Lambda@Edge strips out the Authorization header and allows the request to pass through to designated origin for CloudFront. In this case, the origin is the private content Amazon S3 bucket.
After receiving response from the origin S3 bucket, CloudFront sends the response back to the browser. The browser displays the data from the returned response.
An example of an Auth@Edge static site configuration is as follows:
variables:
dev:
namespace: sample-app-dev
staticsite_user_pool_arn: arn:aws:cognito-idp:us-east-1:123456789012:userpool/us-east-1_example
deployments:
- modules:
- path: sampleapp
type: static
parameters:
namespace: ${var ${env DEPLOY_ENVIRONMENT}.namespace}
staticsite_auth_at_edge: true
staticsite_user_pool_arn: ${var ${env DEPLOY_ENVIRONMENT}.staticsite_user_pool_arn}
regions:
- us-east-1
The Auth@Edge functionality uses an existing Cognito User Pool (optionally configured with federated identity providers) or can create one for you with the staticsite_create_user_pool option. A user pool app client will be automatically created within the pool for use with the application.
Extra Files
The extra files option allows you to use a single build across many deployments. Some popular front end frameworks guide you into including environment specific parameters as part of the build(e.g. Angular and Redux-React). This forces you to abandon 12 factor principles and slows down deployments to other environments.
The static site extra_files option solves this problem by moving environment configuration out of your code and into Runway.
A small change to the way the application references environment config will need to be made.
While bootstrapping or early in the application lifecycle, make an HTTP call to load one of the
extra_files.Make the content of the
extra_fileavailable to your app using an appropriate abstraction.
See Static Site Examples to see how to do this in Angular and React.
Configuration (extra_files list item)
- name: str
The destination name of the file to create.
- file: Optional[str] = None
A reference to an existing file. The content of this file will be uploaded to the static site S3 bucket using the name as the object key. This or
contentmust be specified.
- content_type: Optional[str] = None
An explicit content type of the file. If not given, the content type will be auto detected based on the name. Only
.json,.yml, and.yamlextensions are recognized automatically.application/jsonto serializecontentinto JSON.text/yamlto serializecontentinto YAML.
- content: Optional[Union[str, List[Any], Dict[str, Any]]] = None
Inline content that will be used as the file content. This or
filemust be specified.
Note
If none of the files or content changed between builds and source hashing is enabled, the upload will be skipped.
Terraform
Runway provides a simple way to run the Terraform versions you want with variable values specific to each environment. Terraform does not need to be installed prior to using this module type. Runway maintains a cache of Terraform versions on a system, downloading and installing different versions as needed.
Configuration
Contents
Options
Options specific to Terraform Modules.
- args: Optional[Union[Dict[str, List[str]], List[str]]] = None
List of CLI arguments/options to pass to Terraform. See Specifying Terraform CLI Arguments/Options for more details.
Example
options: args: - '-parallelism=25'
New in version 1.8.1.
- terraform_backend_config: Optional[Dict[str, str]] = {}
Mapping to configure Terraform backend. See Backend for more details.
Example
options: terraform_backend_config: bucket: mybucket dynamodb_table: mytable region: us-east-1
Changed in version 1.11.0: Added support for any key: value.
- terraform_version: Optional[str] = None
String containing the Terraform version or a mapping of deploy environment to a Terraform version. See Version Management for more details.
Example
options: terraform_version: 0.11.13
- terraform_write_auto_tfvars: Optional[bool] = False
Optionally write parameters to a tfvars file instead of updating variables. This can be useful in cases where Runway may not be parsing/passing parameters as expected.
When
True, Runway creates a temporaryrunway-parameters.auto.tfvars.jsonfile in the module directory. This file contains all of the modules parameters in JSON format. This file is then automatically loaded by Terraform as needed. If using a remote backend, use of this file to pass variables is required as environment variables are not available from the CLI and-var-filecurrently cannot be used. Once the module has finished processing, the file is deleted.Example
options: terraform_write_auto_tfvars: true
New in version 1.11.0.
Variables
Variables can be defined per-environment using one or both of the following options.
tfvars
Standard Terraform tfvars files can be used, exactly as one normally would with terraform apply -var-file.
Runway will automatically detect them when named like ENV-REGION.tfvars or ENV.tfvars.
Example
region = "us-east-1"
image_id = "ami-abc123"
runway.yml
Variable values can also be specified as deployment.parameters/module.parameters values in runway.yml.
It is recommended to use Lookups in the parameters section to assist in selecting the appropriate values for the deploy environment and/or region being deployed to but, this is not a requirement if the value will remain the same.
deployments:
- modules:
- path: sampleapp-01.tf
parameters:
region: ${env AWS_REGION}
image_id: ${var image_id.${env AWS_REGION}}
my_list:
- item1
- item2
my_map:
key1: value1
key2: value1
- modules:
- path: sampleapp-02.tf
parameters:
region: ${env AWS_REGION}
image_id: ${var image_id.${env AWS_REGION}}
my_list:
- item1
- item2
my_map:
key1: value1
key2: value1
Directory Structure
Example directory structures for a Terraform module.
Example
.
├── .terraform-version
├── backend-us-east-1.tfvars
├── dev-us-east-1.tfvars
└── main.tf
Advanced Features
Advanced features and detailed information for using Terraform with Runway.
Contents
Backend Configuration
If your Terraform will only ever be used with a single backend, it can be defined inline.
main.tf
terraform {
backend "s3" {
region = "us-east-1"
key = "some_unique_identifier_for_my_module"
bucket = "some_s3_bucket_name"
dynamodb_table = "some_ddb_table_name"
}
}
However, it’s generally preferable to separate the backend configuration out from the rest of the Terraform code. This form of configuration is known as partial configuration and allows for dynamic or secret values to be passed in at runtime.
Below are examples of how to implement partial configuration with Runway. All examples provided showcase the use of the s3 backend type as it is the easiest to use when going from zero to deployed (try runway gen-sample cfngin for quickstart Terraform backend infrastructure). However, Runway supports the use of any backend type (refer to Terraform’s documentation for proper partial configuration instructions).
See also
- https://www.terraform.io/docs/backends/config.html#partial-configuration
Terraform partial configuration
- https://www.terraform.io/docs/backends/types/index.html
Terraform backend types
Backend Config File
Backend config options can be specified in a separate file or multiple files per environment and/or region using one of the following naming schemes.
backend-ENV-REGION.(hcl|tfvars)
backend-ENV.(hcl|tfvars)
backend-REGION.(hcl|tfvars)
backend.(hcl|tfvars)
Example
region = "us-east-1"
bucket = "some_s3_bucket_name"
dynamodb_table = "some_ddb_table_name"
In the above example, where all but the key are defined, the main.tf backend definition is reduced to the following.
main.tf
terraform {
backend "s3" {
key = "some_unique_identifier_for_my_module"
}
}
Changed in version 1.11.0: Added support for hcl files.
runway.yml
Backend config options can also be specified as a module option in the Runway Config File. Lookups can be used to provide dynamic values to this option.
Important
There has been a bug since Terraform 0.12 that prevents passing blocks to -backend-config (issue).
This means that for backends that use blocks in their config (e.g. remote), the blocks must be provided via file.
Attributes are unaffected.
workspaces {
prefix = "example-"
}
deployments:
- modules:
- path: sampleapp-01.tf
options:
terraform_backend_config:
bucket: mybucket
dynamodb_table: mytable
region: us-east-1
- path: sampleapp-02.tf
options:
terraform_backend_config:
bucket: ${cfn common-tf-state.TerraformStateBucketName}
dynamodb_table: ${cfn common-tf-state.TerraformStateTableName}
region: ${env AWS_REGION}
deployments:
- modules:
- path: sampleapp-01.tf
- path: sampleapp-02.tf
module_options: # shared between all modules in deployment
terraform_backend_config:
bucket: ${ssm ParamNameHere::region=us-east-1}
dynamodb_table: ${ssm ParamNameHere::region=us-east-1}
region: ${env AWS_REGION}
Specifying Terraform CLI Arguments/Options
Runway can pass custom arguments/options to the Terraform CLI by using the args option.
The value of args can be provided in one of two ways.
The simplest way is to provide a list of arguments/options which will be appended to terraform apply when executed by Runway.
Each element of the argument/option should be it’s own list item (e.g. -parallelism=25 -no-color would be ['-parallelism=25, '-no-color']).
For more control, a map can be provided to pass arguments/options to other commands.
Arguments can be passed to terraform apply, terraform init, and/or terraform plan by using the action as the key in the map (see the Runway Example section below).
The value of each key in the map must be a list as described in the previous section.
Important
The following arguments/options are provided by Runway and should not be provided manually: auto-approve, backend-config, force, no-color, reconfigure, update, and var-file. Providing any of these manually could result in unintended side-effects.
deployments:
- modules:
- path: sampleapp-01.tf
options:
args:
- '-no-color'
- '-parallelism=25'
- path: sampleapp-02.tf
options:
args:
apply:
- '-no-color'
- '-parallelism=25'
init:
- '-no-color'
plan:
- '-no-color'
- '-parallelism=25'
regions:
- us-east-2
environments:
example: true
# runway deploy - sampleapp-01.tf
terraform init -reconfigure
terraform apply -no-color -parallelism=25 -auto-approve=false
# runway plan - sampleapp-01.tf
terraform plan
# runway deploy - sampleapp-02.tf
terraform init -reconfigure -no-color
terraform apply -no-color -parallelism=25 -auto-approve=false
# runway plan - sampleapp-02.tf
terraform plan -no-color -parallelism=25
Version Management
By specifying which version of Terraform to use via a .terraform-version file in your module directory or in deployment.module_options/module.options, Runway will automatically download & use that version for the module.
This, alongside tightly pinning Terraform provider versions, is highly recommended to keep a predictable experience when deploying your module.
0.11.6
deployments:
- modules:
- path: sampleapp-01.tf
options:
terraform_version: 0.11.13
Without a version specified, Runway will fallback to whatever terraform it finds first in your PATH.
API Docs
runway package
Set package version.
Subpackages
Support for AWS SSO.
IMPORTANT: This will be removed upon botocore/boto3 officially supporting authentication with AWS SSO profiles.
The code in this directory is taken from https://github.com/boto/botocore/tree/bf6d31f42f90a547707df4e83943702beacda45a and modified to meet the requirements of this project.
Botocore with support for AWS SSO credential assets.
- runway.aws_sso_botocore.credentials.create_credential_resolver(session, cache=None, region_name=None)[source]
Create a default credential resolver.
This creates a pre-configured credential resolver that includes the default lookup chain for credentials.
- class runway.aws_sso_botocore.credentials.ProfileProviderBuilder[source]
Bases:
botocore.credentials.ProfileProviderBuilderExtends the botocore profile provider builder to support AWS SSO.
- __new__(**kwargs)
- class runway.aws_sso_botocore.credentials.SSOCredentialFetcher[source]
Bases:
botocore.credentials.CachedCredentialFetcherAWS SSO credential fetcher.
- __init__(start_url, sso_region, role_name, account_id, client_creator, token_loader=None, cache=None, expiry_window_seconds=None)[source]
Instantiate class.
- __new__(**kwargs)
Botocore with support for AWS SSO exceptions.
- exception runway.aws_sso_botocore.exceptions.SSOError[source]
Bases:
botocore.exceptions.BotoCoreErrorBase class for AWS SSO authentication errors.
- __init__(**kwargs)
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.aws_sso_botocore.exceptions.PendingAuthorizationExpiredError[source]
Bases:
runway.aws_sso_botocore.exceptions.SSOErrorPending AWS SSO authorization expired.
- __init__(**kwargs)
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
Botocore with support for AWS SSO session assets.
- class runway.aws_sso_botocore.session.Session[source]
Bases:
botocore.session.SessionExtends the botocore session to support AWS SSO.
- __init__(session_vars=None, event_hooks=None, include_builtin_handlers=True, profile=None)[source]
Create a new Session object.
- Parameters
session_vars (dict) – A dictionary that is used to override some or all of the environment variables associated with this session. The key/value pairs defined in this dictionary will override the corresponding variables defined in
SESSION_VARIABLES.event_hooks (BaseEventHooks) – The event hooks object to use. If one is not provided, an event hooks object will be automatically created for you.
include_builtin_handlers (bool) – Indicates whether or not to automatically register builtin handlers.
profile (str) – The name of the profile to use for this session. Note that the profile can only be set when the session is created.
- __new__(**kwargs)
- create_client(service_name, region_name=None, api_version=None, use_ssl=True, verify=None, endpoint_url=None, aws_access_key_id=None, aws_secret_access_key=None, aws_session_token=None, config=None)[source]
Create a botocore client.
- Parameters
service_name (string) – The name of the service for which a client will be created. You can use the
Session.get_available_services()method to get a list of all available service names.region_name (string) – The name of the region associated with the client. A client is associated with a single region.
api_version (string) – The API version to use. By default, botocore will use the latest API version when creating a client. You only need to specify this parameter if you want to use a previous API version of the client.
use_ssl (boolean) – Whether or not to use SSL. By default, SSL is used. Note that not all services support non-ssl connections.
verify (boolean/string) –
Whether or not to verify SSL certificates. By default SSL certificates are verified. You can provide the following values:
False - do not validate SSL certificates. SSL will still be used (unless use_ssl is False), but SSL certificates will not be verified.
path/to/cert/bundle.pem - A filename of the CA cert bundle to uses. You can specify this argument if you want to use a different CA cert bundle than the one used by botocore.
endpoint_url (string) – The complete URL to use for the constructed client. Normally, botocore will automatically construct the appropriate URL to use when communicating with a service. You can specify a complete URL (including the “http/https” scheme) to override this behavior. If this value is provided, then
use_sslis ignored.aws_access_key_id (string) – The access key to use when creating the client. This is entirely optional, and if not provided, the credentials configured for the session will automatically be used. You only need to provide this argument if you want to override the credentials used for this specific client.
aws_secret_access_key (string) – The secret key to use when creating the client. Same semantics as aws_access_key_id above.
aws_session_token (string) – The session token to use when creating the client. Same semantics as aws_access_key_id above.
config (botocore.client.Config) – Advanced client configuration options. If a value is specified in the client config, its value will take precedence over environment variables and configuration values, but not over a value passed explicitly to the method. If a default config object is set on the session, the config object used when creating the client will be the result of calling
merge()on the default config with the config provided to this call.
- Return type
botocore.client.BaseClient
- Returns
A botocore client instance
- property full_config
Return the parsed config file.
The
get_configmethod returns the config associated with the specified profile. This property returns the contents of the entire config file.- Return type
- get_auth_token()[source]
Return the
botocore.tokens.AuthTokenobject associated with this session. If the authorization token has not yet been loaded, this will attempt to load it. If it has already been loaded, this will return the cached authorization token.
- get_available_partitions()[source]
Lists the available partitions found on disk
- Return type
- Returns
Returns a list of partition names (e.g., [“aws”, “aws-cn”])
- get_available_regions(service_name, partition_name='aws', allow_non_regional=False)[source]
Lists the region and endpoint names of a particular partition.
- Parameters
service_name (string) – Name of a service to list endpoint for (e.g., s3). This parameter accepts a service name (e.g., “elb”) or endpoint prefix (e.g., “elasticloadbalancing”).
partition_name (string) – Name of the partition to limit endpoints to. (e.g., aws for the public AWS endpoints, aws-cn for AWS China endpoints, aws-us-gov for AWS GovCloud (US) Endpoints, etc.
allow_non_regional (bool) – Set to True to include endpoints that are not regional endpoints (e.g., s3-external-1, fips-us-gov-west-1, etc).
- Returns
Returns a list of endpoint names (e.g., [“us-east-1”]).
- get_credentials()[source]
Return the
botocore.credential.Credentialobject associated with this session. If the credentials have not yet been loaded, this will attempt to load them. If they have already been loaded, this will return the cached credentials.
- get_data(data_path)[source]
Retrieve the data associated with data_path.
- Parameters
data_path (str) – The path to the data you wish to retrieve.
- get_default_client_config()[source]
Retrieves the default config for creating clients
- Return type
botocore.client.Config
- Returns
The default client config object when creating clients. If the value is
Nonethen there is no default config object attached to the session.
- get_partition_for_region(region_name)[source]
Lists the partition name of a particular region.
- Parameters
region_name (string) – Name of the region to list partition for (e.g., us-east-1).
- Return type
string
- Returns
Returns the respective partition name (e.g., aws).
- get_scoped_config()[source]
Returns the config values from the config file scoped to the current profile.
The configuration data is loaded only from the config file. It does not resolve variables based on different locations (e.g. first from the session instance, then from environment variables, then from the config file). If you want this lookup behavior, use the
get_config_variablemethod instead.Note that this configuration is specific to a single profile (the
profilesession variable).If the
profilesession variable is set and the profile does not exist in the config file, aProfileNotFoundexception will be raised.- Raises
ConfigNotFound, ConfigParseError, ProfileNotFound
- Return type
- get_service_data(service_name, api_version=None)[source]
Retrieve the fully merged data associated with a service.
- get_service_model(service_name, api_version=None)[source]
Get the service model object.
- Parameters
service_name (string) – The service name
api_version (string) – The API version of the service. If none is provided, then the latest API version will be used.
- Return type
L{botocore.model.ServiceModel}
- Returns
The botocore service model for the service.
- register(event_name, handler, unique_id=None, unique_id_uses_count=False)[source]
Register a handler with an event.
- Parameters
event_name (str) – The name of the event.
handler (callable) – The callback to invoke when the event is emitted. This object must be callable, and must accept
**kwargs. If either of these preconditions are not met, aValueErrorwill be raised.unique_id (str) – An optional identifier to associate with the registration. A unique_id can only be used once for the entire session registration (unless it is unregistered). This can be used to prevent an event handler from being registered twice.
unique_id_uses_count – boolean
unique_id_uses_count – Specifies if the event should maintain a count when a
unique_idis registered and unregisted. The event can only be completely unregistered once every register call using the unique id has been matched by anunregistercall. Ifunique_idis specified, subsequentregistercalls must use the same value forunique_id_uses_countas theregistercall that first registered the event.
- Raises
ValueError – If the call to
registerusesunique_idbut the value forunique_id_uses_countdiffers from theunique_id_uses_countvalue declared by the very firstregistercall for thatunique_id.
- set_config_variable(logical_name, value)[source]
Set a configuration variable to a specific value.
By using this method, you can override the normal lookup process used in
get_config_variableby explicitly setting a value. Subsequent calls toget_config_variablewill use thevalue. This gives you per-session specific configuration values.- ::
>>> # Assume logical name 'foo' maps to env var 'FOO' >>> os.environ['FOO'] = 'myvalue' >>> s.get_config_variable('foo') 'myvalue' >>> s.set_config_variable('foo', 'othervalue') >>> s.get_config_variable('foo') 'othervalue'
- Parameters
logical_name (str) – The logical name of the session variable you want to set. These are the keys in
SESSION_VARIABLES.value – The value to associate with the config variable.
- set_credentials(access_key, secret_key, token=None)[source]
Manually create credentials for this session. If you would prefer to use botocore without a config file, environment variables, or IAM roles, you can pass explicit credentials into this method to establish credentials for this session.
- set_debug_logger(logger_name='botocore')[source]
Convenience function to quickly configure full debug output to go to the console.
- set_default_client_config(client_config)[source]
Sets the default config for creating clients
- Parameters
client_config (botocore.client.Config) – The default client config object when creating clients. If the value is
Nonethen there is no default config object attached to the session.
- set_file_logger(log_level, path, logger_name='botocore')[source]
Convenience function to quickly configure any level of logging to a file.
- Parameters
log_level (int) – A log level as specified in the logging module
path (string) – Path to the log file. The file will be created if it doesn’t already exist.
- set_stream_logger(logger_name, log_level, stream=None, format_string=None)[source]
Convenience method to configure a stream logger.
- Parameters
logger_name (str) – The name of the logger to configure
log_level (str) – The log level to set for the logger. This is any param supported by the
.setLevel()method of aLogobject.stream (file) – A file like object to log to. If none is provided then sys.stderr will be used.
format_string (str) – The format string to use for the log formatter. If none is provided this will default to
self.LOG_FORMAT.
- unregister(event_name, handler=None, unique_id=None, unique_id_uses_count=False)[source]
Unregister a handler with an event.
- Parameters
event_name (str) – The name of the event.
handler (callable) – The callback to unregister.
unique_id (str) – A unique identifier identifying the callback to unregister. You can provide either the handler or the unique_id, you do not have to provide both.
unique_id_uses_count – boolean
unique_id_uses_count – Specifies if the event should maintain a count when a
unique_idis registered and unregisted. The event can only be completely unregistered once everyregistercall using theunique_idhas been matched by anunregistercall. If theunique_idis specified, subsequentunregistercalls must use the same value forunique_id_uses_countas theregistercall that first registered the event.
- Raises
ValueError – If the call to
unregisterusesunique_idbut the value forunique_id_uses_countdiffers from theunique_id_uses_countvalue declared by the very firstregistercall for thatunique_id.
- user_agent()[source]
Return a string suitable for use as a User-Agent header. The string will be of the form:
<agent_name>/<agent_version> Python/<py_ver> <plat_name>/<plat_ver> <exec_env>
Where:
agent_name is the value of the user_agent_name attribute of the session object (Botocore by default).
agent_version is the value of the user_agent_version attribute of the session object (the botocore version by default). by default.
py_ver is the version of the Python interpreter beng used.
plat_name is the name of the platform (e.g. Darwin)
plat_ver is the version of the platform
exec_env is exec-env/$AWS_EXECUTION_ENV
If
user_agent_extrais not empty, then this value will be appended to the end of the user agent string.
Botocore with support for AWS SSO utilities.
Empty init for python import traversal.
Empty init for python import traversal.
Module with k8s IAM resources.
- class runway.blueprints.k8s.k8s_iam.Iam[source]
Bases:
runway.cfngin.blueprints.base.BlueprintCFNgin blueprint for creating k8s IAM resources.
- __init__(name: str, context: runway.context.CfnginContext, *, description: Optional[str] = None, mappings: Optional[Dict[str, Dict[str, Any]]] = None, template: Optional[troposphere.Template] = None, **_: Any)
Instantiate class.
- Parameters
name – A name for the blueprint.
context – Context the blueprint is being executed under.
description – The description of the CloudFormation template that will be generated by this blueprint.
mappings – CloudFormation Mappings to be used in the template during the rendering process.
template – Optionally, provide a preexisting Template.
Changed in version 2.0.0: Added
template.Changed in version 2.0.0: Class only takes 2 positional arguments. The rest are now keyword arguments.
- __new__(**kwargs)
- add_output(name: str, value: Any) None
Add an output to the template.
Wrapper for
self.template.add_output(Output(name, Value=value)).- Parameters
name – The name of the output to create.
value – The value to put in the output.
- property cfn_parameters: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters.
- property defined_variables: Dict[str, BlueprintVariableTypeDef]
Return a copy of
VARIABLESto avoid accidental modification of the ClassVar.Changed in version 2.0.0: Changed from a method to a property.
- get_cfn_parameters() Dict[str, Union[List[Any], str]]
Return a dictionary of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
cfn_parameters.- Returns
Variables that need to be submitted as CloudFormation Parameters.
- get_output_definitions() Dict[str, Dict[str, Any]]
Get the output definitions.
Deprecated since version 2.0.0: Replaced by
output_definitions.- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- get_parameter_definitions() Dict[str, BlueprintVariableTypeDef]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.Deprecated since version 2.0.0: Replaced by
parameter_definitions.- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- get_parameter_values() Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
parameter_values.- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- get_required_parameter_definitions() Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
Deprecated since version 2.0.0: Replaced by
required_parameter_definitions.- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- get_variables() Dict[str, Any]
Return a dictionary of variables available to the template.
These variables will have been defined within VARIABLES or self.defined_variables. Any variable value that contains a lookup will have been resolved.
Deprecated since version 2.0.0: Replaced by
variables.- Returns
Variables available to the template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
- property output_definitions: Dict[str, Dict[str, Any]]
Get the output definitions.
New in version 2.0.0.
- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- property parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.New in version 2.0.0.
- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- property parameter_values: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- read_user_data(user_data_path: str) str
Read and parse a user_data file.
- Parameters
user_data_path – Path to the userdata file.
- property required_parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
New in version 2.0.0.
- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- resolve_variables(provided_variables: List[runway.variables.Variable]) None
Resolve the values of the blueprint variables.
This will resolve the values of the VARIABLES with values from the env file, the config, and any lookups resolved.
- Parameters
provided_variables – List of provided variables.
- set_template_description(description: str) None
Add a description to the Template.
- Parameters
description – A description to be added to the resulting template.
- to_json(variables: Optional[Dict[str, Any]] = None) str
Render the blueprint and return the template in json form.
- Parameters
variables – Dictionary providing/overriding variable values.
- property variables: Dict[str, Any]
Return a Dict of variables available to the Template.
These variables will have been defined within
VARIABLESordefined_variables. Any variable value that contains a Lookup will have been resolved.New in version 2.0.0.
- Returns
Variables available to the Template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
Module with k8s cluster resources.
- class runway.blueprints.k8s.k8s_master.Cluster[source]
Bases:
runway.cfngin.blueprints.base.BlueprintCFNgin blueprint for creating k8s cluster resources.
- __init__(name: str, context: runway.context.CfnginContext, *, description: Optional[str] = None, mappings: Optional[Dict[str, Dict[str, Any]]] = None, template: Optional[troposphere.Template] = None, **_: Any)
Instantiate class.
- Parameters
name – A name for the blueprint.
context – Context the blueprint is being executed under.
description – The description of the CloudFormation template that will be generated by this blueprint.
mappings – CloudFormation Mappings to be used in the template during the rendering process.
template – Optionally, provide a preexisting Template.
Changed in version 2.0.0: Added
template.Changed in version 2.0.0: Class only takes 2 positional arguments. The rest are now keyword arguments.
- __new__(**kwargs)
- add_output(name: str, value: Any) None
Add an output to the template.
Wrapper for
self.template.add_output(Output(name, Value=value)).- Parameters
name – The name of the output to create.
value – The value to put in the output.
- property cfn_parameters: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters.
- property defined_variables: Dict[str, BlueprintVariableTypeDef]
Return a copy of
VARIABLESto avoid accidental modification of the ClassVar.Changed in version 2.0.0: Changed from a method to a property.
- get_cfn_parameters() Dict[str, Union[List[Any], str]]
Return a dictionary of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
cfn_parameters.- Returns
Variables that need to be submitted as CloudFormation Parameters.
- get_output_definitions() Dict[str, Dict[str, Any]]
Get the output definitions.
Deprecated since version 2.0.0: Replaced by
output_definitions.- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- get_parameter_definitions() Dict[str, BlueprintVariableTypeDef]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.Deprecated since version 2.0.0: Replaced by
parameter_definitions.- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- get_parameter_values() Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
parameter_values.- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- get_required_parameter_definitions() Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
Deprecated since version 2.0.0: Replaced by
required_parameter_definitions.- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- get_variables() Dict[str, Any]
Return a dictionary of variables available to the template.
These variables will have been defined within VARIABLES or self.defined_variables. Any variable value that contains a lookup will have been resolved.
Deprecated since version 2.0.0: Replaced by
variables.- Returns
Variables available to the template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
- property output_definitions: Dict[str, Dict[str, Any]]
Get the output definitions.
New in version 2.0.0.
- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- property parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.New in version 2.0.0.
- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- property parameter_values: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- read_user_data(user_data_path: str) str
Read and parse a user_data file.
- Parameters
user_data_path – Path to the userdata file.
- property required_parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
New in version 2.0.0.
- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- resolve_variables(provided_variables: List[runway.variables.Variable]) None
Resolve the values of the blueprint variables.
This will resolve the values of the VARIABLES with values from the env file, the config, and any lookups resolved.
- Parameters
provided_variables – List of provided variables.
- set_template_description(description: str) None
Add a description to the Template.
- Parameters
description – A description to be added to the resulting template.
- to_json(variables: Optional[Dict[str, Any]] = None) str
Render the blueprint and return the template in json form.
- Parameters
variables – Dictionary providing/overriding variable values.
- property variables: Dict[str, Any]
Return a Dict of variables available to the Template.
These variables will have been defined within
VARIABLESordefined_variables. Any variable value that contains a Lookup will have been resolved.New in version 2.0.0.
- Returns
Variables available to the Template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
Module with k8s nodegroup.
- runway.blueprints.k8s.k8s_workers.get_valid_instance_types() Any[source]
Return list of instance types from either a JSON or gzipped JSON file.
- class runway.blueprints.k8s.k8s_workers.NodeGroup[source]
Bases:
runway.cfngin.blueprints.base.BlueprintCFNgin blueprint for creating k8s nodegroup.
- __init__(name: str, context: runway.context.CfnginContext, *, description: Optional[str] = None, mappings: Optional[Dict[str, Dict[str, Any]]] = None, template: Optional[troposphere.Template] = None, **_: Any)
Instantiate class.
- Parameters
name – A name for the blueprint.
context – Context the blueprint is being executed under.
description – The description of the CloudFormation template that will be generated by this blueprint.
mappings – CloudFormation Mappings to be used in the template during the rendering process.
template – Optionally, provide a preexisting Template.
Changed in version 2.0.0: Added
template.Changed in version 2.0.0: Class only takes 2 positional arguments. The rest are now keyword arguments.
- __new__(**kwargs)
- add_output(name: str, value: Any) None
Add an output to the template.
Wrapper for
self.template.add_output(Output(name, Value=value)).- Parameters
name – The name of the output to create.
value – The value to put in the output.
- property cfn_parameters: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters.
- property defined_variables: Dict[str, BlueprintVariableTypeDef]
Return a copy of
VARIABLESto avoid accidental modification of the ClassVar.Changed in version 2.0.0: Changed from a method to a property.
- get_cfn_parameters() Dict[str, Union[List[Any], str]]
Return a dictionary of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
cfn_parameters.- Returns
Variables that need to be submitted as CloudFormation Parameters.
- get_output_definitions() Dict[str, Dict[str, Any]]
Get the output definitions.
Deprecated since version 2.0.0: Replaced by
output_definitions.- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- get_parameter_definitions() Dict[str, BlueprintVariableTypeDef]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.Deprecated since version 2.0.0: Replaced by
parameter_definitions.- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- get_parameter_values() Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
parameter_values.- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- get_required_parameter_definitions() Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
Deprecated since version 2.0.0: Replaced by
required_parameter_definitions.- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- get_variables() Dict[str, Any]
Return a dictionary of variables available to the template.
These variables will have been defined within VARIABLES or self.defined_variables. Any variable value that contains a lookup will have been resolved.
Deprecated since version 2.0.0: Replaced by
variables.- Returns
Variables available to the template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
- property output_definitions: Dict[str, Dict[str, Any]]
Get the output definitions.
New in version 2.0.0.
- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- property parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.New in version 2.0.0.
- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- property parameter_values: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- read_user_data(user_data_path: str) str
Read and parse a user_data file.
- Parameters
user_data_path – Path to the userdata file.
- property required_parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
New in version 2.0.0.
- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- resolve_variables(provided_variables: List[runway.variables.Variable]) None
Resolve the values of the blueprint variables.
This will resolve the values of the VARIABLES with values from the env file, the config, and any lookups resolved.
- Parameters
provided_variables – List of provided variables.
- set_template_description(description: str) None
Add a description to the Template.
- Parameters
description – A description to be added to the resulting template.
- to_json(variables: Optional[Dict[str, Any]] = None) str
Render the blueprint and return the template in json form.
- Parameters
variables – Dictionary providing/overriding variable values.
- property variables: Dict[str, Any]
Return a Dict of variables available to the Template.
These variables will have been defined within
VARIABLESordefined_variables. Any variable value that contains a Lookup will have been resolved.New in version 2.0.0.
- Returns
Variables available to the Template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
Empty init for python import traversal.
Blueprint for the Authorization@Edge implementation of a Static Site.
Described in detail in this blogpost: https://aws.amazon.com/blogs/networking-and-content-delivery/authorizationedge-how-to-use-lambdaedge-and-json-web-tokens-to-enhance-web-application-security/
- class runway.blueprints.staticsite.auth_at_edge.AuthAtEdge[source]
Bases:
runway.blueprints.staticsite.staticsite.StaticSiteAuth@Edge Blueprint.
- __init__(name: str, context: runway.context.CfnginContext, mappings: Optional[Dict[str, Dict[str, Any]]] = None, description: Optional[str] = None) None[source]
Initialize the Blueprint.
- Parameters
name – A name for the blueprint.
context – Context the blueprint is being executed under.
mappings – CloudFormation Mappings to be used in the template.
description – Used to describe the resulting CloudFormation template.
- get_auth_at_edge_lambda_and_ver(title: str, description: str, handle: str, role: troposphere.iam.Role) Dict[str, Any][source]
Create a lambda function and its version.
- Parameters
title – The name of the function in PascalCase.
description – Description to be displayed in the lambda panel.
handle – The underscore separated representation of the name of the lambda. This handle is used to determine the handler for the lambda as well as identify the correct Code hook_data information.
role – The Lambda Execution Role.
- get_auth_at_edge_lambda(title: str, description: str, handler: str, role: troposphere.iam.Role) troposphere.awslambda.Function[source]
Create an Auth@Edge lambda resource.
- Parameters
title – The name of the function in PascalCase.
description – Description to be displayed in the lambda panel.
handler – The underscore separated representation of the name of the lambda. This handle is used to determine the handler for the lambda as well as identify the correct Code hook_data information.
role – The Lambda Execution Role.
- add_version(title: str, lambda_function: troposphere.awslambda.Function) troposphere.awslambda.Version[source]
Create a version association with a Lambda@Edge function.
In order to ensure different versions of the function are appropriately uploaded a hash based on the code of the lambda is appended to the name. As the code changes so will this hash value.
- Parameters
title – The name of the function in PascalCase.
lambda_function – The Lambda function.
- get_distribution_options(bucket: troposphere.s3.Bucket, oai: troposphere.cloudfront.CloudFrontOriginAccessIdentity, lambda_funcs: List[troposphere.cloudfront.LambdaFunctionAssociation], check_auth_lambda_version: troposphere.awslambda.Version, http_headers_lambda_version: troposphere.awslambda.Version, parse_auth_lambda_version: troposphere.awslambda.Version, refresh_auth_lambda_version: troposphere.awslambda.Version, sign_out_lambda_version: troposphere.awslambda.Version) Dict[str, Any][source]
Retrieve the options for our CloudFront distribution.
- Keyword Arguments
bucket – The bucket resource.
oai – The origin access identity resource.
lambda_funcs – List of Lambda Function associations.
check_auth_lambda_version – Lambda Function Version to use.
http_headers_lambda_version – Lambda Function Version to use.
parse_auth_lambda_version – Lambda Function Version to use.
refresh_auth_lambda_version – Lambda Function Version to use.
sign_out_lambda_version – Lambda Function Version to use.
- Returns
The CloudFront Distribution Options.
- __new__(**kwargs)
- add_acm_cert() Union[cloudfront.ViewerCertificate, Ref]
Add ACM cert.
- add_bucket() troposphere.s3.Bucket
Add the bucket resource along with an output of it’s name / website url.
- Returns
The bucket resource.
- add_bucket_policy(bucket: troposphere.s3.Bucket) troposphere.s3.BucketPolicy
Add a policy to the bucket if CloudFront is disabled. Ensure PublicRead.
- Parameters
bucket – The bucket resource to place the policy.
- Returns
The Bucket Policy Resource.
- add_cloudfront_bucket_policy(bucket: troposphere.s3.Bucket, oai: troposphere.cloudfront.CloudFrontOriginAccessIdentity) troposphere.s3.BucketPolicy
Given a bucket and oai resource add cloudfront access to the bucket.
- Keyword Arguments
bucket – A bucket resource.
oai – An Origin Access Identity resource.
- Returns
The CloudFront Bucket access resource.
- add_cloudfront_directory_index_rewrite(role: troposphere.iam.Role) troposphere.awslambda.Function
Add an index CloudFront directory index rewrite lambda function to the template.
- Keyword Arguments
role – The index rewrite role resource.
- Returns
The CloudFront directory index rewrite lambda function resource.
- add_cloudfront_directory_index_rewrite_version(directory_index_rewrite: troposphere.awslambda.Function) troposphere.awslambda.Version
Add a specific version to the directory index rewrite lambda.
- Parameters
directory_index_rewrite – The directory index rewrite lambda resource.
- Returns
The CloudFront directory index rewrite version.
- add_cloudfront_distribution(bucket_policy: troposphere.s3.BucketPolicy, cloudfront_distribution_options: Dict[str, Any]) troposphere.cloudfront.Distribution
Add the CloudFront distribution to the template / output the id and domain name.
- Parameters
bucket_policy – Bucket policy to allow CloudFront access.
cloudfront_distribution_options – The distribution options.
- Returns
The CloudFront Distribution resource
- add_lambda_execution_role(name: str = 'LambdaExecutionRole', function_name: str = '') troposphere.iam.Role
Create the Lambda@Edge execution role.
- Parameters
name – Name for the Lambda Execution Role.
function_name – Name of the Lambda Function the Role will be attached to.
- add_logging_bucket() Union[cloudfront.Logging, Ref]
Add Logging Bucket.
- add_origin_access_identity() troposphere.cloudfront.CloudFrontOriginAccessIdentity
Add the origin access identity resource to the template.
- add_output(name: str, value: Any) None
Add an output to the template.
Wrapper for
self.template.add_output(Output(name, Value=value)).- Parameters
name – The name of the output to create.
value – The value to put in the output.
- property cfn_parameters: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters.
- property defined_variables: Dict[str, BlueprintVariableTypeDef]
Return a copy of
VARIABLESto avoid accidental modification of the ClassVar.Changed in version 2.0.0: Changed from a method to a property.
- get_cfn_parameters() Dict[str, Union[List[Any], str]]
Return a dictionary of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
cfn_parameters.- Returns
Variables that need to be submitted as CloudFormation Parameters.
- get_cloudfront_distribution_options(bucket: troposphere.s3.Bucket, oai: troposphere.cloudfront.CloudFrontOriginAccessIdentity, lambda_function_associations: List[troposphere.cloudfront.LambdaFunctionAssociation]) Dict[str, Any]
Retrieve the options for our CloudFront distribution.
- Parameters
bucket – The bucket resource
oai – The origin access identity resource.
lambda_function_associations – List of Lambda Function associations.
- Returns
The CloudFront Distribution Options.
- static get_directory_index_lambda_association(lambda_associations: List[troposphere.cloudfront.LambdaFunctionAssociation], directory_index_rewrite_version: troposphere.awslambda.Version) List[troposphere.cloudfront.LambdaFunctionAssociation]
Retrieve the directory index lambda associations with the added rewriter.
- Parameters
lambda_associations – The lambda associations.
directory_index_rewrite_version – The directory index rewrite version.
- get_lambda_associations() List[troposphere.cloudfront.LambdaFunctionAssociation]
Retrieve any lambda associations from the instance variables.
- get_output_definitions() Dict[str, Dict[str, Any]]
Get the output definitions.
Deprecated since version 2.0.0: Replaced by
output_definitions.- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- get_parameter_definitions() Dict[str, BlueprintVariableTypeDef]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.Deprecated since version 2.0.0: Replaced by
parameter_definitions.- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- get_parameter_values() Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
parameter_values.- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- get_required_parameter_definitions() Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
Deprecated since version 2.0.0: Replaced by
required_parameter_definitions.- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- get_variables() Dict[str, Any]
Return a dictionary of variables available to the template.
These variables will have been defined within VARIABLES or self.defined_variables. Any variable value that contains a lookup will have been resolved.
Deprecated since version 2.0.0: Replaced by
variables.- Returns
Variables available to the template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
- property output_definitions: Dict[str, Dict[str, Any]]
Get the output definitions.
New in version 2.0.0.
- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- property parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.New in version 2.0.0.
- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- property parameter_values: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- read_user_data(user_data_path: str) str
Read and parse a user_data file.
- Parameters
user_data_path – Path to the userdata file.
- property required_parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
New in version 2.0.0.
- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- resolve_variables(provided_variables: List[runway.variables.Variable]) None
Resolve the values of the blueprint variables.
This will resolve the values of the VARIABLES with values from the env file, the config, and any lookups resolved.
- Parameters
provided_variables – List of provided variables.
- set_template_description(description: str) None
Add a description to the Template.
- Parameters
description – A description to be added to the resulting template.
- to_json(variables: Optional[Dict[str, Any]] = None) str
Render the blueprint and return the template in json form.
- Parameters
variables – Dictionary providing/overriding variable values.
- property variables: Dict[str, Any]
Return a Dict of variables available to the Template.
These variables will have been defined within
VARIABLESordefined_variables. Any variable value that contains a Lookup will have been resolved.New in version 2.0.0.
- Returns
Variables available to the Template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
Module with static website supporting infrastructure.
- class runway.blueprints.staticsite.dependencies.Dependencies[source]
Bases:
runway.cfngin.blueprints.base.BlueprintCFNgin blueprint for creating static website buckets.
- __init__(name: str, context: runway.context.CfnginContext, *, description: Optional[str] = None, mappings: Optional[Dict[str, Dict[str, Any]]] = None, template: Optional[troposphere.Template] = None, **_: Any)
Instantiate class.
- Parameters
name – A name for the blueprint.
context – Context the blueprint is being executed under.
description – The description of the CloudFormation template that will be generated by this blueprint.
mappings – CloudFormation Mappings to be used in the template during the rendering process.
template – Optionally, provide a preexisting Template.
Changed in version 2.0.0: Added
template.Changed in version 2.0.0: Class only takes 2 positional arguments. The rest are now keyword arguments.
- __new__(**kwargs)
- add_output(name: str, value: Any) None
Add an output to the template.
Wrapper for
self.template.add_output(Output(name, Value=value)).- Parameters
name – The name of the output to create.
value – The value to put in the output.
- property cfn_parameters: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters.
- property defined_variables: Dict[str, BlueprintVariableTypeDef]
Return a copy of
VARIABLESto avoid accidental modification of the ClassVar.Changed in version 2.0.0: Changed from a method to a property.
- get_cfn_parameters() Dict[str, Union[List[Any], str]]
Return a dictionary of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
cfn_parameters.- Returns
Variables that need to be submitted as CloudFormation Parameters.
- get_output_definitions() Dict[str, Dict[str, Any]]
Get the output definitions.
Deprecated since version 2.0.0: Replaced by
output_definitions.- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- get_parameter_definitions() Dict[str, BlueprintVariableTypeDef]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.Deprecated since version 2.0.0: Replaced by
parameter_definitions.- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- get_parameter_values() Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
parameter_values.- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- get_required_parameter_definitions() Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
Deprecated since version 2.0.0: Replaced by
required_parameter_definitions.- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- get_variables() Dict[str, Any]
Return a dictionary of variables available to the template.
These variables will have been defined within VARIABLES or self.defined_variables. Any variable value that contains a lookup will have been resolved.
Deprecated since version 2.0.0: Replaced by
variables.- Returns
Variables available to the template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
- property output_definitions: Dict[str, Dict[str, Any]]
Get the output definitions.
New in version 2.0.0.
- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- property parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.New in version 2.0.0.
- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- property parameter_values: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- read_user_data(user_data_path: str) str
Read and parse a user_data file.
- Parameters
user_data_path – Path to the userdata file.
- property required_parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
New in version 2.0.0.
- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- resolve_variables(provided_variables: List[runway.variables.Variable]) None
Resolve the values of the blueprint variables.
This will resolve the values of the VARIABLES with values from the env file, the config, and any lookups resolved.
- Parameters
provided_variables – List of provided variables.
- set_template_description(description: str) None
Add a description to the Template.
- Parameters
description – A description to be added to the resulting template.
- to_json(variables: Optional[Dict[str, Any]] = None) str
Render the blueprint and return the template in json form.
- Parameters
variables – Dictionary providing/overriding variable values.
- property variables: Dict[str, Any]
Return a Dict of variables available to the Template.
These variables will have been defined within
VARIABLESordefined_variables. Any variable value that contains a Lookup will have been resolved.New in version 2.0.0.
- Returns
Variables available to the Template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
Module with static website bucket and CloudFront distribution.
- class runway.blueprints.staticsite.staticsite.StaticSite[source]
Bases:
runway.cfngin.blueprints.base.BlueprintCFNgin blueprint for creating S3 bucket and CloudFront distribution.
- get_lambda_associations() List[troposphere.cloudfront.LambdaFunctionAssociation][source]
Retrieve any lambda associations from the instance variables.
- static get_directory_index_lambda_association(lambda_associations: List[troposphere.cloudfront.LambdaFunctionAssociation], directory_index_rewrite_version: troposphere.awslambda.Version) List[troposphere.cloudfront.LambdaFunctionAssociation][source]
Retrieve the directory index lambda associations with the added rewriter.
- Parameters
lambda_associations – The lambda associations.
directory_index_rewrite_version – The directory index rewrite version.
- get_cloudfront_distribution_options(bucket: troposphere.s3.Bucket, oai: troposphere.cloudfront.CloudFrontOriginAccessIdentity, lambda_function_associations: List[troposphere.cloudfront.LambdaFunctionAssociation]) Dict[str, Any][source]
Retrieve the options for our CloudFront distribution.
- Parameters
bucket – The bucket resource
oai – The origin access identity resource.
lambda_function_associations – List of Lambda Function associations.
- Returns
The CloudFront Distribution Options.
- add_origin_access_identity() troposphere.cloudfront.CloudFrontOriginAccessIdentity[source]
Add the origin access identity resource to the template.
- add_bucket_policy(bucket: troposphere.s3.Bucket) troposphere.s3.BucketPolicy[source]
Add a policy to the bucket if CloudFront is disabled. Ensure PublicRead.
- Parameters
bucket – The bucket resource to place the policy.
- Returns
The Bucket Policy Resource.
- add_bucket() troposphere.s3.Bucket[source]
Add the bucket resource along with an output of it’s name / website url.
- Returns
The bucket resource.
- add_cloudfront_bucket_policy(bucket: troposphere.s3.Bucket, oai: troposphere.cloudfront.CloudFrontOriginAccessIdentity) troposphere.s3.BucketPolicy[source]
Given a bucket and oai resource add cloudfront access to the bucket.
- Keyword Arguments
bucket – A bucket resource.
oai – An Origin Access Identity resource.
- Returns
The CloudFront Bucket access resource.
- add_lambda_execution_role(name: str = 'LambdaExecutionRole', function_name: str = '') troposphere.iam.Role[source]
Create the Lambda@Edge execution role.
- Parameters
name – Name for the Lambda Execution Role.
function_name – Name of the Lambda Function the Role will be attached to.
- add_cloudfront_directory_index_rewrite(role: troposphere.iam.Role) troposphere.awslambda.Function[source]
Add an index CloudFront directory index rewrite lambda function to the template.
- Keyword Arguments
role – The index rewrite role resource.
- Returns
The CloudFront directory index rewrite lambda function resource.
- add_cloudfront_directory_index_rewrite_version(directory_index_rewrite: troposphere.awslambda.Function) troposphere.awslambda.Version[source]
Add a specific version to the directory index rewrite lambda.
- Parameters
directory_index_rewrite – The directory index rewrite lambda resource.
- Returns
The CloudFront directory index rewrite version.
- add_cloudfront_distribution(bucket_policy: troposphere.s3.BucketPolicy, cloudfront_distribution_options: Dict[str, Any]) troposphere.cloudfront.Distribution[source]
Add the CloudFront distribution to the template / output the id and domain name.
- Parameters
bucket_policy – Bucket policy to allow CloudFront access.
cloudfront_distribution_options – The distribution options.
- Returns
The CloudFront Distribution resource
- __init__(name: str, context: runway.context.CfnginContext, *, description: Optional[str] = None, mappings: Optional[Dict[str, Dict[str, Any]]] = None, template: Optional[troposphere.Template] = None, **_: Any)
Instantiate class.
- Parameters
name – A name for the blueprint.
context – Context the blueprint is being executed under.
description – The description of the CloudFormation template that will be generated by this blueprint.
mappings – CloudFormation Mappings to be used in the template during the rendering process.
template – Optionally, provide a preexisting Template.
Changed in version 2.0.0: Added
template.Changed in version 2.0.0: Class only takes 2 positional arguments. The rest are now keyword arguments.
- __new__(**kwargs)
- add_output(name: str, value: Any) None
Add an output to the template.
Wrapper for
self.template.add_output(Output(name, Value=value)).- Parameters
name – The name of the output to create.
value – The value to put in the output.
- property cfn_parameters: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters.
- property defined_variables: Dict[str, BlueprintVariableTypeDef]
Return a copy of
VARIABLESto avoid accidental modification of the ClassVar.Changed in version 2.0.0: Changed from a method to a property.
- get_cfn_parameters() Dict[str, Union[List[Any], str]]
Return a dictionary of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
cfn_parameters.- Returns
Variables that need to be submitted as CloudFormation Parameters.
- get_output_definitions() Dict[str, Dict[str, Any]]
Get the output definitions.
Deprecated since version 2.0.0: Replaced by
output_definitions.- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- get_parameter_definitions() Dict[str, BlueprintVariableTypeDef]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.Deprecated since version 2.0.0: Replaced by
parameter_definitions.- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- get_parameter_values() Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
parameter_values.- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- get_required_parameter_definitions() Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
Deprecated since version 2.0.0: Replaced by
required_parameter_definitions.- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- get_variables() Dict[str, Any]
Return a dictionary of variables available to the template.
These variables will have been defined within VARIABLES or self.defined_variables. Any variable value that contains a lookup will have been resolved.
Deprecated since version 2.0.0: Replaced by
variables.- Returns
Variables available to the template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
- property output_definitions: Dict[str, Dict[str, Any]]
Get the output definitions.
New in version 2.0.0.
- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- property parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.New in version 2.0.0.
- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- property parameter_values: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- read_user_data(user_data_path: str) str
Read and parse a user_data file.
- Parameters
user_data_path – Path to the userdata file.
- property required_parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
New in version 2.0.0.
- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- resolve_variables(provided_variables: List[runway.variables.Variable]) None
Resolve the values of the blueprint variables.
This will resolve the values of the VARIABLES with values from the env file, the config, and any lookups resolved.
- Parameters
provided_variables – List of provided variables.
- set_template_description(description: str) None
Add a description to the Template.
- Parameters
description – A description to be added to the resulting template.
- to_json(variables: Optional[Dict[str, Any]] = None) str
Render the blueprint and return the template in json form.
- Parameters
variables – Dictionary providing/overriding variable values.
- property variables: Dict[str, Any]
Return a Dict of variables available to the Template.
These variables will have been defined within
VARIABLESordefined_variables. Any variable value that contains a Lookup will have been resolved.New in version 2.0.0.
- Returns
Variables available to the Template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
Module with Terraform state resources.
- class runway.blueprints.tf_state.TfState[source]
Bases:
runway.cfngin.blueprints.base.BlueprintCFNgin blueprint for creating Terraform state resources.
- __init__(name: str, context: runway.context.CfnginContext, *, description: Optional[str] = None, mappings: Optional[Dict[str, Dict[str, Any]]] = None, template: Optional[troposphere.Template] = None, **_: Any)
Instantiate class.
- Parameters
name – A name for the blueprint.
context – Context the blueprint is being executed under.
description – The description of the CloudFormation template that will be generated by this blueprint.
mappings – CloudFormation Mappings to be used in the template during the rendering process.
template – Optionally, provide a preexisting Template.
Changed in version 2.0.0: Added
template.Changed in version 2.0.0: Class only takes 2 positional arguments. The rest are now keyword arguments.
- __new__(**kwargs)
- add_output(name: str, value: Any) None
Add an output to the template.
Wrapper for
self.template.add_output(Output(name, Value=value)).- Parameters
name – The name of the output to create.
value – The value to put in the output.
- property cfn_parameters: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters.
- property defined_variables: Dict[str, BlueprintVariableTypeDef]
Return a copy of
VARIABLESto avoid accidental modification of the ClassVar.Changed in version 2.0.0: Changed from a method to a property.
- get_cfn_parameters() Dict[str, Union[List[Any], str]]
Return a dictionary of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
cfn_parameters.- Returns
Variables that need to be submitted as CloudFormation Parameters.
- get_output_definitions() Dict[str, Dict[str, Any]]
Get the output definitions.
Deprecated since version 2.0.0: Replaced by
output_definitions.- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- get_parameter_definitions() Dict[str, BlueprintVariableTypeDef]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.Deprecated since version 2.0.0: Replaced by
parameter_definitions.- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- get_parameter_values() Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
parameter_values.- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- get_required_parameter_definitions() Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
Deprecated since version 2.0.0: Replaced by
required_parameter_definitions.- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- get_variables() Dict[str, Any]
Return a dictionary of variables available to the template.
These variables will have been defined within VARIABLES or self.defined_variables. Any variable value that contains a lookup will have been resolved.
Deprecated since version 2.0.0: Replaced by
variables.- Returns
Variables available to the template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
- property output_definitions: Dict[str, Dict[str, Any]]
Get the output definitions.
New in version 2.0.0.
- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- property parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.New in version 2.0.0.
- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- property parameter_values: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- read_user_data(user_data_path: str) str
Read and parse a user_data file.
- Parameters
user_data_path – Path to the userdata file.
- property required_parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
New in version 2.0.0.
- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- resolve_variables(provided_variables: List[runway.variables.Variable]) None
Resolve the values of the blueprint variables.
This will resolve the values of the VARIABLES with values from the env file, the config, and any lookups resolved.
- Parameters
provided_variables – List of provided variables.
- set_template_description(description: str) None
Add a description to the Template.
- Parameters
description – A description to be added to the resulting template.
- to_json(variables: Optional[Dict[str, Any]] = None) str
Render the blueprint and return the template in json form.
- Parameters
variables – Dictionary providing/overriding variable values.
- property variables: Dict[str, Any]
Return a Dict of variables available to the Template.
These variables will have been defined within
VARIABLESordefined_variables. Any variable value that contains a Lookup will have been resolved.New in version 2.0.0.
- Returns
Variables available to the Template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
Empty init for python import traversal.
Import modules.
CFNgin base action.
- runway.cfngin.actions.base.build_walker(concurrency: int) Callable[[...], Any][source]
Return a function for waling a graph.
Passed to
runway.cfngin.plan.Planfor walking the graph.If concurrency is 1 (no parallelism) this will return a simple topological walker that doesn’t use any multithreading.
If concurrency is 0, this will return a walker that will walk the graph as fast as the graph topology allows.
If concurrency is greater than 1, it will return a walker that will only execute a maximum of concurrency steps at any given time.
- Parameters
concurrency – Number of threads to use while walking.
- Returns
Function to walk a
runway.cfngin.dag.DAG.
- runway.cfngin.actions.base.stack_template_url(bucket_name: str, blueprint: Blueprint, endpoint: str)[source]
Produce an s3 url for a given blueprint.
- Parameters
bucket_name – The name of the S3 bucket where the resulting templates are stored.
blueprint – The blueprint object to create the URL to.
endpoint – The s3 endpoint used for the bucket.
- class runway.cfngin.actions.base.BaseAction[source]
Bases:
objectActions perform the actual work of each Command.
Each action is responsible for building the
runway.cfngin.plan.Planthat will be executed.- cancel
Cancel handler.
- Type
- context
The context for the current run.
- Type
- provider_builder
An object that will build a provider that will be interacted with in order to perform the necessary actions.
- Type
Optional[ProviderBuilder]
- s3_conn
Boto3 S3 client.
- Type
S3Client
- __init__(context: CfnginContext, provider_builder: Optional[ProviderBuilder] = None, cancel: Optional[threading.Event] = None)[source]
Instantiate class.
- Parameters
context – The context for the current run.
provider_builder – An object that will build a provider that will be interacted with in order to perform the necessary actions.
cancel – Cancel handler.
- property provider: Provider
Return a generic provider using the default region.
Used for running things like hooks.
- __new__(**kwargs)
- pre_run(*, dump: Union[bool, str] = False, outline: bool = False, **_BaseAction__kwargs: Any) None[source]
Perform steps before running the action.
- post_run(*, dump: Union[bool, str] = False, outline: bool = False, **_BaseAction__kwargs: Any) None[source]
Perform steps after running the action.
- run(*, concurrency: int = 0, dump: Union[bool, str] = False, force: bool = False, outline: bool = False, tail: bool = False, upload_disabled: bool = False, **_kwargs: Any) None[source]
Abstract method for running the action.
CFNgin deploy action.
- runway.cfngin.actions.deploy.build_stack_tags(stack: Stack) List[TagTypeDef][source]
Build a common set of tags to attach to a stack.
- runway.cfngin.actions.deploy.should_update(stack: Stack) bool[source]
Test whether a stack should be submitted for updates to CloudFormation.
- Parameters
stack – The stack object to check.
- runway.cfngin.actions.deploy.should_submit(stack: Stack) bool[source]
Test whether a stack should be submitted to CF for update/create.
- Parameters
stack – The stack object to check.
- runway.cfngin.actions.deploy.should_ensure_cfn_bucket(outline: bool, dump: bool) bool[source]
Test whether access to the cloudformation template bucket is required.
- Parameters
outline – The outline action.
dump – The dump action.
- Returns
If access to CF bucket is needed, return True.
- class runway.cfngin.actions.deploy.UsePreviousParameterValue[source]
Bases:
objectClass used to indicate a Parameter should use it’s existing value.
- __init__()
- __new__(**kwargs)
- runway.cfngin.actions.deploy.handle_hooks(stage: Literal['post_deploy', 'pre_deploy'], hooks: List[CfnginHookDefinitionModel], provider: Provider, context: CfnginContext, *, dump: Union[bool, str] = False, outline: bool = False) None[source]
Handle pre/post hooks.
- Parameters
stage – The name of the hook stage - pre_deploy/post_deploy.
hooks – A list of dictionaries containing the hooks to execute.
provider – The provider the current stack is using.
context – The current CFNgin context.
dump – Whether running with dump set or not.
outline – Whether running with outline set or not.
- class runway.cfngin.actions.deploy.Action[source]
Bases:
runway.cfngin.actions.base.BaseActionResponsible for building & deploying CloudFormation stacks.
Generates the deploy plan based on stack dependencies (these dependencies are determined automatically based on output lookups from other stacks).
The plan can then either be printed out as an outline or executed. If executed, each stack will get launched in order which entails:
Pushing the generated CloudFormation template to S3 if it has changed
Submitting either a create or update of the given stack to the
runway.cfngin.providers.base.BaseProvider.
- static build_parameters(stack: Stack, provider_stack: Optional[StackTypeDef] = None) List[ParameterTypeDef][source]
Build the CloudFormation Parameters for our stack.
- Parameters
stack – A CFNgin stack.
provider_stack – An optional CFNgin provider object.
- Returns
The parameters for the given stack
- pre_run(*, dump: Union[bool, str] = False, outline: bool = False, **_: Any) None[source]
Any steps that need to be taken prior to running the action.
- run(*, concurrency: int = 0, dump: Union[bool, str] = False, force: bool = False, outline: bool = False, tail: bool = False, upload_disabled: bool = False, **_kwargs: Any) None[source]
Kicks off the create/update of the stacks in the stack_definitions.
This is the main entry point for the action.
- Parameters
concurrency – The maximum number of concurrent deployments.
dump – Dump the plan rather than execute it.
force – Not used by this action.
outline – Outline the plan rather than execute it.
tail – Tail the stack’s events.
upload_disabled – Whether to explicitly disable uploading the CloudFormation template to S3.
- __init__(context: CfnginContext, provider_builder: Optional[ProviderBuilder] = None, cancel: Optional[threading.Event] = None)
Instantiate class.
- Parameters
context – The context for the current run.
provider_builder – An object that will build a provider that will be interacted with in order to perform the necessary actions.
cancel – Cancel handler.
- __new__(**kwargs)
- post_run(*, dump: Union[bool, str] = False, outline: bool = False, **_: Any) None[source]
Any steps that need to be taken after running the action.
- property provider: Provider
Return a generic provider using the default region.
Used for running things like hooks.
CFNgin destroy action.
- class runway.cfngin.actions.destroy.Action[source]
Bases:
runway.cfngin.actions.base.BaseActionResponsible for destroying CloudFormation stacks.
Generates a destruction plan based on stack dependencies. Stack dependencies are reversed from the deploy action. For example, if a Stack B requires Stack A during deploy, during destroy Stack A requires Stack B be destroyed first.
The plan defaults to printing an outline of what will be destroyed. If forced to execute, each stack will get destroyed in order.
- pre_run(*, dump: Union[bool, str] = False, outline: bool = False, **_Action__kwargs: Any) None[source]
Any steps that need to be taken prior to running the action.
- run(*, concurrency: int = 0, dump: Union[bool, str] = False, force: bool = False, outline: bool = False, tail: bool = False, upload_disabled: bool = False, **_kwargs: Any) None[source]
Kicks off the destruction of the stacks in the stack_definitions.
- post_run(*, dump: Union[bool, str] = False, outline: bool = False, **_Action__kwargs: Any) None[source]
Any steps that need to be taken after running the action.
- __init__(context: CfnginContext, provider_builder: Optional[ProviderBuilder] = None, cancel: Optional[threading.Event] = None)
Instantiate class.
- Parameters
context – The context for the current run.
provider_builder – An object that will build a provider that will be interacted with in order to perform the necessary actions.
cancel – Cancel handler.
- __new__(**kwargs)
- property provider: Provider
Return a generic provider using the default region.
Used for running things like hooks.
CFNgin diff action.
- class runway.cfngin.actions.diff.DictValue[source]
Bases:
Generic[runway.cfngin.actions.diff._OV,runway.cfngin.actions.diff._NV]Used to create a diff of two dictionaries.
- __init__(key: str, old_value: runway.cfngin.actions.diff._OV, new_value: runway.cfngin.actions.diff._NV) None[source]
Instantiate class.
- changes() List[str][source]
Return changes to represent the diff between old and new value.
- Returns
Representation of the change (if any) between old and new value.
- __new__(**kwargs)
- runway.cfngin.actions.diff.diff_dictionaries(old_dict: Dict[str, runway.cfngin.actions.diff._OV], new_dict: Dict[str, runway.cfngin.actions.diff._NV]) Tuple[int, List[runway.cfngin.actions.diff.DictValue[runway.cfngin.actions.diff._OV, runway.cfngin.actions.diff._NV]]][source]
Calculate the diff two single dimension dictionaries.
- Parameters
old_dict – Old dictionary.
new_dict – New dictionary.
- Returns
Number of changed records and the
DictValueobject containing the changes.
- runway.cfngin.actions.diff.format_params_diff(parameter_diff: List[runway.cfngin.actions.diff.DictValue[Any, Any]]) str[source]
Handle the formatting of differences in parameters.
- Parameters
parameter_diff – A list of
DictValuedetailing the differences between two dicts returned bydiff_dictionaries().- Returns
A formatted string that represents a parameter diff
- runway.cfngin.actions.diff.diff_parameters(old_params: Dict[str, runway.cfngin.actions.diff._OV], new_params: Dict[str, runway.cfngin.actions.diff._NV]) List[runway.cfngin.actions.diff.DictValue[runway.cfngin.actions.diff._OV, runway.cfngin.actions.diff._NV]][source]
Compare the old vs. new parameters and returns a “diff”.
If there are no changes, we return an empty list.
- Parameters
old_params – old parameters
new_params – new parameters
- Returns
A list of differences.
- class runway.cfngin.actions.diff.Action[source]
Bases:
runway.cfngin.actions.deploy.ActionResponsible for diffing CloudFormation stacks in AWS and locally.
Generates the deploy plan based on stack dependencies (these dependencies are determined automatically based on references to output values from other stacks).
The plan is then used to create a changeset for a stack using a generated template based on the current config.
- run(*, concurrency: int = 0, dump: Union[bool, str] = False, force: bool = False, outline: bool = False, tail: bool = False, upload_disabled: bool = False, **_kwargs: Any) None[source]
Kicks off the diffing of the stacks in the stack_definitions.
- pre_run(*, dump: Union[bool, str] = False, outline: bool = False, **_Action__kwargs: Any) None[source]
Any steps that need to be taken prior to running the action.
Handle CFNgin bucket access denied & not existing.
- post_run(*, dump: Union[bool, str] = False, outline: bool = False, **_Action__kwargs: Any) None[source]
Do nothing.
- __init__(context: CfnginContext, provider_builder: Optional[ProviderBuilder] = None, cancel: Optional[threading.Event] = None)
Instantiate class.
- Parameters
context – The context for the current run.
provider_builder – An object that will build a provider that will be interacted with in order to perform the necessary actions.
cancel – Cancel handler.
- __new__(**kwargs)
- static build_parameters(stack: Stack, provider_stack: Optional[StackTypeDef] = None) List[ParameterTypeDef][source]
Build the CloudFormation Parameters for our stack.
- Parameters
stack – A CFNgin stack.
provider_stack – An optional CFNgin provider object.
- Returns
The parameters for the given stack
- property provider: Provider
Return a generic provider using the default region.
Used for running things like hooks.
CFNgin graph action.
- runway.cfngin.actions.graph.each_step(graph: Graph) Iterable[Tuple[Step, List[Step]]][source]
Yield each step and it’s direct dependencies.
- Parameters
graph – Graph to iterate over.
- runway.cfngin.actions.graph.dot_format(out: TextIO, graph: Graph, name: str = 'digraph') None[source]
Output a graph using the graphviz “dot” format.
- Parameters
out – Where output will be written.
graph – Graph to be output.
name – Name of the graph.
- runway.cfngin.actions.graph.json_format(out: TextIO, graph: Graph) None[source]
Output the graph in a machine readable JSON format.
- Parameters
out – Where output will be written.
graph – Graph to be output.
- class runway.cfngin.actions.graph.Action[source]
Bases:
runway.cfngin.actions.base.BaseActionResponsible for outputting a graph for the current CFNgin config.
- run(*, concurrency: int = 0, dump: Union[bool, str] = False, force: bool = False, outline: bool = False, tail: bool = False, upload_disabled: bool = False, **kwargs: Any) None[source]
Generate the underlying graph and prints it.
- __init__(context: CfnginContext, provider_builder: Optional[ProviderBuilder] = None, cancel: Optional[threading.Event] = None)
Instantiate class.
- Parameters
context – The context for the current run.
provider_builder – An object that will build a provider that will be interacted with in order to perform the necessary actions.
cancel – Cancel handler.
- __new__(**kwargs)
- post_run(*, dump: Union[bool, str] = False, outline: bool = False, **_BaseAction__kwargs: Any) None
Perform steps after running the action.
- pre_run(*, dump: Union[bool, str] = False, outline: bool = False, **_BaseAction__kwargs: Any) None
Perform steps before running the action.
- property provider: Provider
Return a generic provider using the default region.
Used for running things like hooks.
CFNgin info action.
- class runway.cfngin.actions.info.Action[source]
Bases:
runway.cfngin.actions.base.BaseActionGet information on CloudFormation stacks.
Displays the outputs for the set of CloudFormation stacks.
- __init__(context: CfnginContext, provider_builder: Optional[ProviderBuilder] = None, cancel: Optional[threading.Event] = None)
Instantiate class.
- Parameters
context – The context for the current run.
provider_builder – An object that will build a provider that will be interacted with in order to perform the necessary actions.
cancel – Cancel handler.
- __new__(**kwargs)
- post_run(*, dump: Union[bool, str] = False, outline: bool = False, **_BaseAction__kwargs: Any) None
Perform steps after running the action.
- pre_run(*, dump: Union[bool, str] = False, outline: bool = False, **_BaseAction__kwargs: Any) None
Perform steps before running the action.
- property provider: Provider
Return a generic provider using the default region.
Used for running things like hooks.
CFNgin init action.
- class runway.cfngin.actions.init.Action[source]
Bases:
runway.cfngin.actions.base.BaseActionInitialize environment.
- __init__(context: CfnginContext, provider_builder: Optional[ProviderBuilder] = None, cancel: Optional[threading.Event] = None)[source]
Instantiate class.
This class creates a copy of the context object prior to initialization as some of it can perform destructive actions on the context object.
- Parameters
context – The context for the current run.
provider_builder – An object that will build a provider that will be interacted with in order to perform the necessary actions.
cancel – Cancel handler.
- property cfngin_bucket: Optional[runway.core.providers.aws.s3._bucket.Bucket]
CFNgin bucket.
- Raises
CfnginBucketRequired – cfngin_bucket not defined.
- property default_cfngin_bucket_stack: runway.config.models.cfngin.CfnginStackDefinitionModel
CFNgin bucket stack.
- run(*, concurrency: int = 0, dump: Union[bool, str] = False, force: bool = False, outline: bool = False, tail: bool = False, upload_disabled: bool = True, **_kwargs: Any) None[source]
Run the action.
- Parameters
concurrency – The maximum number of concurrent deployments.
dump – Not used by this action
force – Not used by this action.
outline – Not used by this action.
tail – Tail the stack’s events.
upload_disabled – Not used by this action.
- Raises
CfnginBucketAccessDenied – Could not head cfngin_bucket.
- pre_run(*, dump: Union[bool, str] = False, outline: bool = False, **_Action__kwargs: Any) None[source]
Do nothing.
- post_run(*, dump: Union[bool, str] = False, outline: bool = False, **_Action__kwargs: Any) None[source]
Do nothing.
- __new__(**kwargs)
- property provider: Provider
Return a generic provider using the default region.
Used for running things like hooks.
Import modules.
Import modules.
CFNgin blueprint variable types.
- class runway.cfngin.blueprints.variables.types.TroposphereType[source]
Bases:
Generic[runway.cfngin.blueprints.variables.types.TroposphereT]Represents a Troposphere type.
Tropospherewill convert the value provided to the variable to the specified Troposphere type.Both resource and parameter classes (which are just used to configure other resources) are acceptable as configuration values.
Complete resource definitions must be dictionaries, with the keys identifying the resource titles, and the values being used as the constructor parameters.
Parameter classes can be defined as dictionary or a list of dictionaries. In either case, the keys and values will be used directly as constructor parameters.
- __init__(defined_type: Type[runway.cfngin.blueprints.variables.types.TroposphereT], *, many: bool = False, optional: bool = False, validate: bool = True) None[source]
Instantiate class.
- Parameters
defined_type – Troposphere type.
many – Whether or not multiple resources can be constructed. If the defined type is a resource, multiple resources can be passed as a dictionary of dictionaries. If it is a parameter class, multiple resources are passed as a list.
optional – Whether an undefined/null configured value is acceptable. In that case a value of
Nonewill be passed to the template, even ifmanyis enabled.validate – Whether to validate the generated object on creation. Should be left enabled unless the object will be augmented with mandatory parameters in the template code, such that it must be validated at a later point.
- create(value: Dict[str, Any]) runway.cfngin.blueprints.variables.types.TroposphereT[source]
- create(value: List[Dict[str, Any]]) List[runway.cfngin.blueprints.variables.types.TroposphereT]
- create(value: None) None
Create the troposphere type from the value.
- Parameters
value – A dictionary or list of dictionaries (see class documentation for details) to use as parameters to create the Troposphere type instance. Each dictionary will be passed to the
from_dictmethod of the type.- Returns
Returns the value converted to the troposphere type.
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.CFNType[source]
Bases:
objectRepresents a CloudFormation Parameter Type.
CFNTypecan be used as thetypefor a Blueprint variable. Unlike other variables, a variable withtype: CFNType, will be submitted to CloudFormation as a Parameter.- parameter_type
Name of the CloudFormation Parameter type to specify when submitting as a CloudFormation Parameter.
- Type
ClassVar[str]
See also
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/parameters-section-structure.html
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.CFNString[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA literal string.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.CFNNumber[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeAn integer or float.
AWS CloudFormation validates the parameter value as a number; however, when you use the parameter elsewhere in your template (for example, by using the Ref intrinsic function), the parameter value becomes a string.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.CFNNumberList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeAn array of integers or floats that are separated by commas.
AWS CloudFormation validates the parameter value as numbers; however, when you use the parameter elsewhere in your template (for example, by using the Ref intrinsic function), the parameter value becomes a list of strings.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.CFNCommaDelimitedList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeAn array of literal strings that are separated by commas.
The total number of strings should be one more than the total number of commas. Also, each member string is space trimmed.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.EC2AvailabilityZoneName[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeAn Availability Zone, such as us-west-2a.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.EC2ImageId[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeAn Amazon EC2 image ID, such as ami-0ff8a91507f77f867.
Note that the AWS CloudFormation console doesn’t show a drop-down list of values for this parameter type.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.EC2InstanceId[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeAn Amazon EC2 instance ID, such as i-1e731a32.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.EC2KeyPairKeyName[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeAn Amazon EC2 key pair name.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.EC2SecurityGroupGroupName[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeAn EC2-Classic or default VPC security group name, such as my-sg-abc.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.EC2SecurityGroupId[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA security group ID, such as sg-a123fd85.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.EC2SubnetId[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA subnet ID, such as subnet-123a351e.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.EC2VolumeId[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeAn Amazon EBS volume ID, such as vol-3cdd3f56.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.EC2VPCId[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA VPC ID, such as vpc-a123baa3.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.Route53HostedZoneId[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeAn Amazon Route 53 hosted zone ID, such as Z23YXV4OVPL04A.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.EC2AvailabilityZoneNameList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeAn array of Availability Zones for a region, such as us-west-2a, us-west-2b.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.EC2ImageIdList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeAn array of Amazon EC2 image IDs, such as ami-0ff8a91507f77f867, ami-0a584ac55a7631c0c.
Note that the AWS CloudFormation console doesn’t show a drop-down list of values for this parameter type.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.EC2InstanceIdList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeAn array of Amazon EC2 instance IDs, such as i-1e731a32, i-1e731a34.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.EC2SecurityGroupGroupNameList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeAn array of EC2-Classic or default VPC security group names.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.EC2SecurityGroupIdList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeAn array of security group IDs, such as sg-a123fd85, sg-b456fd85.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.EC2SubnetIdList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeAn array of subnet IDs, such as subnet-123a351e, subnet-456b351e.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.EC2VolumeIdList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeAn array of Amazon EBS volume IDs, such as vol-3cdd3f56, vol-4cdd3f56.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.EC2VPCIdList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeAn array of VPC IDs, such as vpc-a123baa3, vpc-b456baa3.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.Route53HostedZoneIdList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeAn array of Amazon Route 53 hosted zone IDs, such as Z23YXV4OVPL04A, Z23YXV4OVPL04B.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterName[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeThe name of a Systems Manager parameter key.
Use this parameter when you want to pass the parameter key. For example, you can use this type to validate that the parameter exists.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueString[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is a string.
This corresponds to the String parameter type in Parameter Store.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueStringList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is a list of strings.
This corresponds to the StringList parameter type in Parameter Store.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueCommaDelimitedList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is a list of strings.
This corresponds to the StringList parameter type in Parameter Store.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueEC2AvailabilityZoneName[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is an AWS-specific parameter type.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueEC2ImageId[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is an AWS-specific parameter type.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueEC2InstanceId[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is an AWS-specific parameter type.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueEC2KeyPairKeyName[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is an AWS-specific parameter type.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueEC2SecurityGroupGroupName[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is an AWS-specific parameter type.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueEC2SecurityGroupId[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is an AWS-specific parameter type.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueEC2SubnetId[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is an AWS-specific parameter type.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueEC2VolumeId[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is an AWS-specific parameter type.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueEC2VPCId[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is an AWS-specific parameter type.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueRoute53HostedZoneId[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is an AWS-specific parameter type.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueEC2AvailabilityZoneNameList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is an AWS-specific parameter type.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueEC2ImageIdList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is an AWS-specific parameter type.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueEC2InstanceIdList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is an AWS-specific parameter type.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueEC2SecurityGroupGroupNameList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is an AWS-specific parameter type.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueEC2SecurityGroupIdList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is an AWS-specific parameter type.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueEC2SubnetIdList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is an AWS-specific parameter type.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueEC2VolumeIdList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is an AWS-specific parameter type.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueEC2VPCIdList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is an AWS-specific parameter type.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.blueprints.variables.types.SSMParameterValueRoute53HostedZoneIdList[source]
Bases:
runway.cfngin.blueprints.variables.types.CFNTypeA Systems Manager parameter whose value is an AWS-specific parameter type.
- __init__()
- __new__(**kwargs)
CFNgin blueprint base classes.
- class runway.cfngin.blueprints.base.CFNParameter[source]
Bases:
objectWrapper around a value to indicate a CloudFormation Parameter.
- __init__(name: str, value: Union[bool, float, int, List[Any], str, Any]) None[source]
Instantiate class.
- Parameters
name – The name of the CloudFormation Parameter.
value – The value we’re going to submit as a CloudFormation Parameter.
- property ref: troposphere.Ref
Ref the value of a parameter.
- to_parameter_value() Union[List[Any], str][source]
Return the value to be submitted to CloudFormation.
- __new__(**kwargs)
- runway.cfngin.blueprints.base.build_parameter(name: str, properties: BlueprintVariableTypeDef) Parameter[source]
Build a troposphere Parameter with the given properties.
- Parameters
name – The name of the parameter.
properties – Contains the properties that will be applied to the parameter. See: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/parameters-section-structure.html
- Returns
The created parameter object.
- runway.cfngin.blueprints.base.validate_variable_type(var_name: str, var_type: Union[Type[runway.cfngin.blueprints.variables.types.CFNType], runway.cfngin.blueprints.variables.types.TroposphereType[Any], type], value: Any) Any[source]
Ensure the value is the correct variable type.
- Parameters
var_name – The name of the defined variable on a blueprint.
var_type – The type that the value should be.
value – The object representing the value provided for the variable
- Returns
The appropriate value object. If the original value was of CFNType, the returned value will be wrapped in CFNParameter.
- Raises
ValueError – If the value isn’t of var_type and can’t be cast as that type, this is raised.
- runway.cfngin.blueprints.base.validate_allowed_values(allowed_values: Optional[List[Any]], value: Any) bool[source]
Support a variable defining which values it allows.
- Parameters
allowed_values – A list of allowed values from the variable definition.
value – The object representing the value provided for the variable.
- Returns
Boolean for whether or not the value is valid.
- runway.cfngin.blueprints.base.resolve_variable(var_name: str, var_def: BlueprintVariableTypeDef, provided_variable: Optional[Variable], blueprint_name: str) Any[source]
Resolve a provided variable value against the variable definition.
- Parameters
var_name – The name of the defined variable on a blueprint.
var_def – A dictionary representing the defined variables attributes.
provided_variable – The variable value provided to the blueprint.
blueprint_name – The name of the blueprint that the variable is being applied to.
- Returns
The resolved variable value, could be any python object.
- Raises
MissingVariable – Raised when a variable with no default is not provided a value.
UnresolvedBlueprintVariable – Raised when the provided variable is not already resolved.
ValueError – Raised when the value is not the right type and cannot be cast as the correct type. Raised by
runway.cfngin.blueprints.base.validate_variable_type()ValidatorError – Raised when a validator raises an exception. Wraps the original exception.
- runway.cfngin.blueprints.base.parse_user_data(variables: Dict[str, Any], raw_user_data: str, blueprint_name: str) str[source]
Parse the given user data and renders it as a template.
It supports referencing template variables to create userdata that’s supplemented with information from the stack, as commonly required when creating EC2 userdata files.
Example
Given a raw_user_data string:
'open file ${file}'And a variables dictionary with:{'file': 'test.txt'}parse_user_data would output:open file test.txt- Parameters
variables – Variables available to the template.
raw_user_data – The user_data to be parsed.
blueprint_name – The name of the blueprint.
- Returns
The parsed user data, with all the variables values and refs replaced with their resolved values.
- Raises
InvalidUserdataPlaceholder – Raised when a placeholder name in raw_user_data is not valid. E.g
${100}would raise this.MissingVariable – Raised when a variable is in the raw_user_data that is not given in the blueprint
- class runway.cfngin.blueprints.base.Blueprint[source]
Bases:
runway.mixins.DelCachedPropMixinBase implementation for rendering a troposphere template.
- VARIABLES
Class variable that defines the values that can be passed from CFNgin to the template. These definition include metadata used to validate the provided value and to propagate the variable to the resulting CloudFormation template.
- Type
ClassVar[Dict[str, BlueprintVariableTypeDef]]
- context
CFNgin context object.
- Type
- description
The description of the CloudFormation template that will be generated by this Blueprint.
- Type
Optional[str]
- mappings
CloudFormation Mappings to be added to the template during the rendering process.
- __init__(name: str, context: runway.context.CfnginContext, *, description: Optional[str] = None, mappings: Optional[Dict[str, Dict[str, Any]]] = None, template: Optional[troposphere.Template] = None, **_: Any)[source]
Instantiate class.
- Parameters
name – A name for the blueprint.
context – Context the blueprint is being executed under.
description – The description of the CloudFormation template that will be generated by this blueprint.
mappings – CloudFormation Mappings to be used in the template during the rendering process.
template – Optionally, provide a preexisting Template.
Changed in version 2.0.0: Added
template.Changed in version 2.0.0: Class only takes 2 positional arguments. The rest are now keyword arguments.
- property cfn_parameters: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters.
- property defined_variables: Dict[str, BlueprintVariableTypeDef]
Return a copy of
VARIABLESto avoid accidental modification of the ClassVar.Changed in version 2.0.0: Changed from a method to a property.
- property output_definitions: Dict[str, Dict[str, Any]]
Get the output definitions.
New in version 2.0.0.
- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- property parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.New in version 2.0.0.
- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- property parameter_values: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- property required_parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
New in version 2.0.0.
- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- property variables: Dict[str, Any]
Return a Dict of variables available to the Template.
These variables will have been defined within
VARIABLESordefined_variables. Any variable value that contains a Lookup will have been resolved.New in version 2.0.0.
- Returns
Variables available to the Template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
- add_output(name: str, value: Any) None[source]
Add an output to the template.
Wrapper for
self.template.add_output(Output(name, Value=value)).- Parameters
name – The name of the output to create.
value – The value to put in the output.
- get_cfn_parameters() Dict[str, Union[List[Any], str]][source]
Return a dictionary of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
cfn_parameters.- Returns
Variables that need to be submitted as CloudFormation Parameters.
- get_output_definitions() Dict[str, Dict[str, Any]][source]
Get the output definitions.
Deprecated since version 2.0.0: Replaced by
output_definitions.- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- get_parameter_definitions() Dict[str, BlueprintVariableTypeDef][source]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.Deprecated since version 2.0.0: Replaced by
parameter_definitions.- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- get_parameter_values() Dict[str, Union[List[Any], str]][source]
Return a dict of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
parameter_values.- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- get_required_parameter_definitions() Dict[str, BlueprintVariableTypeDef][source]
Return all template parameters that do not have a default value.
Deprecated since version 2.0.0: Replaced by
required_parameter_definitions.- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- get_variables() Dict[str, Any][source]
Return a dictionary of variables available to the template.
These variables will have been defined within VARIABLES or self.defined_variables. Any variable value that contains a lookup will have been resolved.
Deprecated since version 2.0.0: Replaced by
variables.- Returns
Variables available to the template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
- __new__(**kwargs)
- read_user_data(user_data_path: str) str[source]
Read and parse a user_data file.
- Parameters
user_data_path – Path to the userdata file.
- resolve_variables(provided_variables: List[runway.variables.Variable]) None[source]
Resolve the values of the blueprint variables.
This will resolve the values of the VARIABLES with values from the env file, the config, and any lookups resolved.
- Parameters
provided_variables – List of provided variables.
CFNgin Bucket Blueprint.
- class runway.cfngin.blueprints.cfngin_bucket.CfnginBucket[source]
Bases:
runway.cfngin.blueprints.base.BlueprintCFNgin Bucket Blueprint.
- property bucket: troposphere.s3.Bucket
CFNgin Bucket.
- property bucket_encryption: Union[AWSHelperFn, s3.BucketEncryption]
CFNgin bucket encryption.
This cached property can be overridden in a subclass to customize the BucketEncryption property of the bucket without needing to override the bucket cached property.
- property bucket_name: AWSHelperFn
CFNgin Bucket name.
- property bucket_tags: troposphere.Tags
CFNgin bucket tags.
This cached property can be overridden in a subclass to customize the Tags property of the bucket without needing to override the bucket cached property.
- __init__(name: str, context: runway.context.CfnginContext, *, description: Optional[str] = None, mappings: Optional[Dict[str, Dict[str, Any]]] = None, template: Optional[troposphere.Template] = None, **_: Any)
Instantiate class.
- Parameters
name – A name for the blueprint.
context – Context the blueprint is being executed under.
description – The description of the CloudFormation template that will be generated by this blueprint.
mappings – CloudFormation Mappings to be used in the template during the rendering process.
template – Optionally, provide a preexisting Template.
Changed in version 2.0.0: Added
template.Changed in version 2.0.0: Class only takes 2 positional arguments. The rest are now keyword arguments.
- __new__(**kwargs)
- add_output(name: str, value: Any) None
Add an output to the template.
Wrapper for
self.template.add_output(Output(name, Value=value)).- Parameters
name – The name of the output to create.
value – The value to put in the output.
- property cfn_parameters: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters.
- property defined_variables: Dict[str, BlueprintVariableTypeDef]
Return a copy of
VARIABLESto avoid accidental modification of the ClassVar.Changed in version 2.0.0: Changed from a method to a property.
- get_cfn_parameters() Dict[str, Union[List[Any], str]]
Return a dictionary of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
cfn_parameters.- Returns
Variables that need to be submitted as CloudFormation Parameters.
- get_output_definitions() Dict[str, Dict[str, Any]]
Get the output definitions.
Deprecated since version 2.0.0: Replaced by
output_definitions.- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- get_parameter_definitions() Dict[str, BlueprintVariableTypeDef]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.Deprecated since version 2.0.0: Replaced by
parameter_definitions.- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- get_parameter_values() Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
parameter_values.- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- get_required_parameter_definitions() Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
Deprecated since version 2.0.0: Replaced by
required_parameter_definitions.- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- get_variables() Dict[str, Any]
Return a dictionary of variables available to the template.
These variables will have been defined within VARIABLES or self.defined_variables. Any variable value that contains a lookup will have been resolved.
Deprecated since version 2.0.0: Replaced by
variables.- Returns
Variables available to the template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
- property output_definitions: Dict[str, Dict[str, Any]]
Get the output definitions.
New in version 2.0.0.
- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- property parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.New in version 2.0.0.
- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- property parameter_values: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- read_user_data(user_data_path: str) str
Read and parse a user_data file.
- Parameters
user_data_path – Path to the userdata file.
- property required_parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
New in version 2.0.0.
- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- resolve_variables(provided_variables: List[runway.variables.Variable]) None
Resolve the values of the blueprint variables.
This will resolve the values of the VARIABLES with values from the env file, the config, and any lookups resolved.
- Parameters
provided_variables – List of provided variables.
- set_template_description(description: str) None
Add a description to the Template.
- Parameters
description – A description to be added to the resulting template.
- to_json(variables: Optional[Dict[str, Any]] = None) str
Render the blueprint and return the template in json form.
- Parameters
variables – Dictionary providing/overriding variable values.
- property variables: Dict[str, Any]
Return a Dict of variables available to the Template.
These variables will have been defined within
VARIABLESordefined_variables. Any variable value that contains a Lookup will have been resolved.New in version 2.0.0.
- Returns
Variables available to the Template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
CFNgin blueprint representing raw template module.
- runway.cfngin.blueprints.raw.get_template_path(file_path: pathlib.Path) Optional[pathlib.Path][source]
Find raw template in working directory or in sys.path.
template_path from config may refer to templates co-located with the CFNgin config, or files in remote package_sources. Here, we emulate python module loading to find the path to the template.
- Parameters
filename – Template path.
- Returns
Path to file, or None if no file found
- runway.cfngin.blueprints.raw.resolve_variable(provided_variable: Optional[Variable], blueprint_name: str) Any[source]
Resolve a provided variable value against the variable definition.
This acts as a subset of resolve_variable logic in the base module, leaving out everything that doesn’t apply to CFN parameters.
- Parameters
provided_variable – The variable value provided to the blueprint.
blueprint_name – The name of the blueprint that the variable is being applied to.
- Raises
UnresolvedBlueprintVariable – Raised when the provided variable is not already resolved.
- class runway.cfngin.blueprints.raw.RawTemplateBlueprint[source]
Bases:
runway.cfngin.blueprints.base.BlueprintBlueprint class for blueprints auto-generated from raw templates.
- context
CFNgin context object.
- description
The description of the CloudFormation template that will be generated by this Blueprint.
- mappings
CloudFormation Mappings to be added to the template during the rendering process.
- name
Name of the Stack that will be created by the Blueprint.
- raw_template_path
Path to the raw CloudFormation template file.
- Type
Path
- __init__(name: str, context: runway.context.CfnginContext, *, description: Optional[str] = None, mappings: Optional[Dict[str, Any]] = None, raw_template_path: pathlib.Path, **_: Any) None[source]
Instantiate class.
Changed in version 2.0.0: Class only takes 2 positional arguments. The rest are now keyword arguments.
- property output_definitions: Dict[str, Dict[str, Any]]
Get the output definitions.
New in version 2.0.0.
- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- property parameter_definitions: Dict[str, Any]
Get the parameter definitions to submit to CloudFormation.
New in version 2.0.0.
- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- property parameter_values: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of
<parameter name>: <parameter value>.
- to_dict() Dict[str, Any][source]
Return the template as a python dictionary.
- Returns
the loaded template as a python dictionary
- Return type
- to_json(variables: Optional[Dict[str, Any]] = None) str[source]
Return the template in JSON.
- Parameters
variables – Unused in this subclass (variables won’t affect the template).
- __new__(**kwargs)
- add_output(name: str, value: Any) None
Add an output to the template.
Wrapper for
self.template.add_output(Output(name, Value=value)).- Parameters
name – The name of the output to create.
value – The value to put in the output.
- property cfn_parameters: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters.
- property defined_variables: Dict[str, BlueprintVariableTypeDef]
Return a copy of
VARIABLESto avoid accidental modification of the ClassVar.Changed in version 2.0.0: Changed from a method to a property.
- get_cfn_parameters() Dict[str, Union[List[Any], str]]
Return a dictionary of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
cfn_parameters.- Returns
Variables that need to be submitted as CloudFormation Parameters.
- get_output_definitions() Dict[str, Dict[str, Any]]
Get the output definitions.
Deprecated since version 2.0.0: Replaced by
output_definitions.- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- get_parameter_definitions() Dict[str, BlueprintVariableTypeDef]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.Deprecated since version 2.0.0: Replaced by
parameter_definitions.- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- get_parameter_values() Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
parameter_values.- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- get_required_parameter_definitions() Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
Deprecated since version 2.0.0: Replaced by
required_parameter_definitions.- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- get_variables() Dict[str, Any]
Return a dictionary of variables available to the template.
These variables will have been defined within VARIABLES or self.defined_variables. Any variable value that contains a lookup will have been resolved.
Deprecated since version 2.0.0: Replaced by
variables.- Returns
Variables available to the template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
- read_user_data(user_data_path: str) str
Read and parse a user_data file.
- Parameters
user_data_path – Path to the userdata file.
- property required_parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
New in version 2.0.0.
- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- resolve_variables(provided_variables: List[Variable]) None[source]
Resolve the values of the blueprint variables.
This will resolve the values of the template parameters with values from the env file, the config, and any lookups resolved. The resolution is run twice, in case the blueprint is jinja2 templated and requires provided variables to render.
- Parameters
provided_variables – List of provided variables.
- set_template_description(description: str) None
Add a description to the Template.
- Parameters
description – A description to be added to the resulting template.
- property variables: Dict[str, Any]
Return a Dict of variables available to the Template.
These variables will have been defined within
VARIABLESordefined_variables. Any variable value that contains a Lookup will have been resolved.New in version 2.0.0.
- Returns
Variables available to the Template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
Provides a subclass of unittest.TestCase for testing blueprints.
- class runway.cfngin.blueprints.testutil.BlueprintTestCase[source]
Bases:
unittest.case.TestCaseExtends the functionality of unittest.TestCase for testing blueprints.
- assertRenderedBlueprint(blueprint: Blueprint) None[source]
Test that the rendered blueprint json matches the expected result.
Result files are to be stored in the repo as
test/fixtures/blueprints/${blueprint.name}.json.
- __init__(methodName='runTest')
Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.
- __new__(**kwargs)
- classmethod addClassCleanup(function, /, *args, **kwargs)
Same as addCleanup, except the cleanup items are called even if setUpClass fails (unlike tearDownClass).
- addCleanup(function, /, *args, **kwargs)
Add a function, with arguments, to be called when the test is completed. Functions added are called on a LIFO basis and are called after tearDown on test failure or success.
Cleanup items are called even if setUp fails (unlike tearDown).
- addTypeEqualityFunc(typeobj, function)
Add a type specific assertEqual style function to compare a type.
This method is for use by TestCase subclasses that need to register their own type equality functions to provide nicer error messages.
- Parameters
typeobj – The data type to call this function on when both values are of the same type in assertEqual().
function – The callable taking two arguments and an optional msg= argument that raises self.failureException with a useful error message when the two arguments are not equal.
- assertAlmostEqual(first, second, places=None, msg=None, delta=None)
Fail if the two objects are unequal as determined by their difference rounded to the given number of decimal places (default 7) and comparing to zero, or by comparing that the difference between the two objects is more than the given delta.
Note that decimal places (from zero) are usually not the same as significant digits (measured from the most significant digit).
If the two objects compare equal then they will automatically compare almost equal.
- assertCountEqual(first, second, msg=None)
Asserts that two iterables have the same elements, the same number of times, without regard to order.
- self.assertEqual(Counter(list(first)),
Counter(list(second)))
- Example:
[0, 1, 1] and [1, 0, 1] compare equal.
[0, 0, 1] and [0, 1] compare unequal.
- assertDictContainsSubset(subset, dictionary, msg=None)
Checks whether dictionary is a superset of subset.
- assertEqual(first, second, msg=None)
Fail if the two objects are unequal as determined by the ‘==’ operator.
- assertFalse(expr, msg=None)
Check that the expression is false.
- assertGreater(a, b, msg=None)
Just like self.assertTrue(a > b), but with a nicer default message.
- assertGreaterEqual(a, b, msg=None)
Just like self.assertTrue(a >= b), but with a nicer default message.
- assertIn(member, container, msg=None)
Just like self.assertTrue(a in b), but with a nicer default message.
- assertIs(expr1, expr2, msg=None)
Just like self.assertTrue(a is b), but with a nicer default message.
- assertIsInstance(obj, cls, msg=None)
Same as self.assertTrue(isinstance(obj, cls)), with a nicer default message.
- assertIsNone(obj, msg=None)
Same as self.assertTrue(obj is None), with a nicer default message.
- assertIsNot(expr1, expr2, msg=None)
Just like self.assertTrue(a is not b), but with a nicer default message.
- assertIsNotNone(obj, msg=None)
Included for symmetry with assertIsNone.
- assertLess(a, b, msg=None)
Just like self.assertTrue(a < b), but with a nicer default message.
- assertLessEqual(a, b, msg=None)
Just like self.assertTrue(a <= b), but with a nicer default message.
- assertListEqual(list1, list2, msg=None)
A list-specific equality assertion.
- Parameters
list1 – The first list to compare.
list2 – The second list to compare.
msg – Optional message to use on failure instead of a list of differences.
- assertLogs(logger=None, level=None)
Fail unless a log message of level level or higher is emitted on logger_name or its children. If omitted, level defaults to INFO and logger defaults to the root logger.
This method must be used as a context manager, and will yield a recording object with two attributes: output and records. At the end of the context manager, the output attribute will be a list of the matching formatted log messages and the records attribute will be a list of the corresponding LogRecord objects.
Example:
with self.assertLogs('foo', level='INFO') as cm: logging.getLogger('foo').info('first message') logging.getLogger('foo.bar').error('second message') self.assertEqual(cm.output, ['INFO:foo:first message', 'ERROR:foo.bar:second message'])
- assertMultiLineEqual(first, second, msg=None)
Assert that two multi-line strings are equal.
- assertNotAlmostEqual(first, second, places=None, msg=None, delta=None)
Fail if the two objects are equal as determined by their difference rounded to the given number of decimal places (default 7) and comparing to zero, or by comparing that the difference between the two objects is less than the given delta.
Note that decimal places (from zero) are usually not the same as significant digits (measured from the most significant digit).
Objects that are equal automatically fail.
- assertNotEqual(first, second, msg=None)
Fail if the two objects are equal as determined by the ‘!=’ operator.
- assertNotIn(member, container, msg=None)
Just like self.assertTrue(a not in b), but with a nicer default message.
- assertNotIsInstance(obj, cls, msg=None)
Included for symmetry with assertIsInstance.
- assertNotRegex(text, unexpected_regex, msg=None)
Fail the test if the text matches the regular expression.
- assertRaises(expected_exception, *args, **kwargs)
Fail unless an exception of class expected_exception is raised by the callable when invoked with specified positional and keyword arguments. If a different type of exception is raised, it will not be caught, and the test case will be deemed to have suffered an error, exactly as for an unexpected exception.
If called with the callable and arguments omitted, will return a context object used like this:
with self.assertRaises(SomeException): do_something()
An optional keyword argument ‘msg’ can be provided when assertRaises is used as a context object.
The context manager keeps a reference to the exception as the ‘exception’ attribute. This allows you to inspect the exception after the assertion:
with self.assertRaises(SomeException) as cm: do_something() the_exception = cm.exception self.assertEqual(the_exception.error_code, 3)
- assertRaisesRegex(expected_exception, expected_regex, *args, **kwargs)
Asserts that the message in a raised exception matches a regex.
- Parameters
expected_exception – Exception class expected to be raised.
expected_regex – Regex (re.Pattern object or string) expected to be found in error message.
args – Function to be called and extra positional args.
kwargs – Extra kwargs.
msg – Optional message used in case of failure. Can only be used when assertRaisesRegex is used as a context manager.
- assertRegex(text, expected_regex, msg=None)
Fail the test unless the text matches the regular expression.
- assertSequenceEqual(seq1, seq2, msg=None, seq_type=None)
An equality assertion for ordered sequences (like lists and tuples).
For the purposes of this function, a valid ordered sequence type is one which can be indexed, has a length, and has an equality operator.
- Parameters
seq1 – The first sequence to compare.
seq2 – The second sequence to compare.
seq_type – The expected datatype of the sequences, or None if no datatype should be enforced.
msg – Optional message to use on failure instead of a list of differences.
- assertSetEqual(set1, set2, msg=None)
A set-specific equality assertion.
- Parameters
set1 – The first set to compare.
set2 – The second set to compare.
msg – Optional message to use on failure instead of a list of differences.
assertSetEqual uses ducktyping to support different types of sets, and is optimized for sets specifically (parameters must support a difference method).
- assertTrue(expr, msg=None)
Check that the expression is true.
- assertTupleEqual(tuple1, tuple2, msg=None)
A tuple-specific equality assertion.
- Parameters
tuple1 – The first tuple to compare.
tuple2 – The second tuple to compare.
msg – Optional message to use on failure instead of a list of differences.
- assertWarns(expected_warning, *args, **kwargs)
Fail unless a warning of class warnClass is triggered by the callable when invoked with specified positional and keyword arguments. If a different type of warning is triggered, it will not be handled: depending on the other warning filtering rules in effect, it might be silenced, printed out, or raised as an exception.
If called with the callable and arguments omitted, will return a context object used like this:
with self.assertWarns(SomeWarning): do_something()
An optional keyword argument ‘msg’ can be provided when assertWarns is used as a context object.
The context manager keeps a reference to the first matching warning as the ‘warning’ attribute; similarly, the ‘filename’ and ‘lineno’ attributes give you information about the line of Python code from which the warning was triggered. This allows you to inspect the warning after the assertion:
with self.assertWarns(SomeWarning) as cm: do_something() the_warning = cm.warning self.assertEqual(the_warning.some_attribute, 147)
- assertWarnsRegex(expected_warning, expected_regex, *args, **kwargs)
Asserts that the message in a triggered warning matches a regexp. Basic functioning is similar to assertWarns() with the addition that only warnings whose messages also match the regular expression are considered successful matches.
- Parameters
expected_warning – Warning class expected to be triggered.
expected_regex – Regex (re.Pattern object or string) expected to be found in error message.
args – Function to be called and extra positional args.
kwargs – Extra kwargs.
msg – Optional message used in case of failure. Can only be used when assertWarnsRegex is used as a context manager.
- debug()
Run the test without collecting errors in a TestResult
- classmethod doClassCleanups()
Execute all class cleanup functions. Normally called for you after tearDownClass.
- doCleanups()
Execute all cleanup functions. Normally called for you after tearDown.
- fail(msg=None)
Fail immediately, with the given message.
- failureException
alias of
AssertionError
- setUp()
Hook method for setting up the test fixture before exercising it.
- classmethod setUpClass()
Hook method for setting up class fixture before running tests in the class.
- shortDescription()
Returns a one-line description of the test, or None if no description has been provided.
The default implementation of this method returns the first line of the specified test method’s docstring.
- skipTest(reason)
Skip this test.
- subTest(msg=<object object>, **params)
Return a context manager that will return the enclosed block of code in a subtest identified by the optional message and keyword parameters. A failure in the subtest marks the test case as failed but resumes execution at the end of the enclosed block, allowing further test code to be executed.
- tearDown()
Hook method for deconstructing the test fixture after testing it.
- classmethod tearDownClass()
Hook method for deconstructing the class fixture after running all tests in the class.
- class runway.cfngin.blueprints.testutil.YamlDirTestGenerator[source]
Bases:
objectGenerate blueprint tests from yaml config files.
This class creates blueprint tests from yaml files with a syntax similar to CFNgin configuration syntax. For example:
namespace: test stacks: - name: test_sample class_path: blueprints.test.Sample variables: var1: value1
Will create a test for the specified blueprint, passing that variable as part of the test.
The test will generate a
.jsonfile for this blueprint, and compare it with the stored result.By default, the generator looks for files named
test_*.yamlin its same directory. In order to use it, subclass it in a directory containing such tests, and name the class with a pattern that will include it in nosetests’ tests (for example, TestGenerator).The subclass may override some
@propertydefinitions:- base_class
By default, the generated tests are subclasses or
runway.cfngin.blueprints.testutil.BlueprintTestCase. In order to change this, set this property to the desired base class.- yaml_dirs:
By default, the directory where the generator is subclassed is searched for test files. Override this array for specifying more directories. These must be relative to the directory in which the subclass lives in. Globs may be used. Default:
['.']. Example override:['.', 'tests/*/']- yaml_filename:
By default, the generator looks for files named
test_*.yaml. Use this to change this pattern. Globs may be used.
- property base_class: Type[runway.cfngin.blueprints.testutil.BlueprintTestCase]
Return the baseclass.
- __new__(**kwargs)
- test_generator() Iterator[runway.cfngin.blueprints.testutil.BlueprintTestCase][source]
Test generator.
CFNgin Blueprint type definitions.
- class runway.cfngin.blueprints.type_defs.BlueprintVariableTypeDef[source]
Bases:
runway.cfngin.blueprints.type_defs._RequiredBlueprintVariableTypeDef,runway.cfngin.blueprints.type_defs._OptionalBlueprintVariableTypeDefType definition for
runway.cfngin.blueprints.base.Blueprint.VARIABLESitems.- allowed_pattern
Only valid for variables whose type subclasses
CFNType. A regular expression that represents the patterns you want to allow for the Cloudformation Parameter.- Type
- allowed_values
Only valid for variables whose type subclasses
CFNType. The values that should be allowed for the CloudFormation Parameter.- Type
List[Any]
- constraint_description
Only valid for variables whose type subclasses
CFNType. A string that explains the constraint when the constraint is violated for the CloudFormation Parameter.- Type
- default
The default value that should be used for the variable if none is provided in the config.
- Type
Any
- max_length
Only valid for variables whose type subclasses
CFNType. The maximum length of the value for the CloudFormation Parameter.- Type
- max_value
Only valid for variables whose type subclasses
CFNType. The max value for the CloudFormation Parameter.- Type
- min_length
Only valid for variables whose type subclasses
CFNType. The minimum length of the value for the CloudFormation Parameter.- Type
- min_value
Only valid for variables whose type subclasses
CFNType. The minimum value for the CloudFormation Parameter.- Type
- no_echo
Only valid for variables whose type subclasses
CFNType. Whether to mask the parameter value whenever anyone makes a call that describes the stack. If you set the value to true, the parameter value is masked with asterisks (*).- Type
- type
The type for the variable value. This can either be a native python type or one of the CFNgin variable types.
- Type
Any
- validator
An optional function that can do custom validation of the variable. A validator function should take a single argument, the value being validated, and should return the value if validation is successful. If there is an issue validating the value, an exception (
ValueError,TypeError, etc) should be raised by the function.- Type
Callable[[Any], Any]
CFNgin directed acyclic graph (DAG) implementation.
- exception runway.cfngin.dag.DAGValidationError[source]
Bases:
ExceptionRaised when DAG validation fails.
- __init__(*args, **kwargs)
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- class runway.cfngin.dag.DAG[source]
Bases:
objectDirected acyclic graph implementation.
- add_node(node_name: str) None[source]
Add a node if it does not exist yet, or error out.
- Parameters
node_name – The unique name of the node to add.
- Raises
KeyError – Raised if a node with the same name already exist in the graph
- add_node_if_not_exists(node_name: str) None[source]
Add a node if it does not exist yet, ignoring duplicates.
- Parameters
node_name – The name of the node to add.
- delete_node(node_name: str) None[source]
Delete this node and all edges referencing it.
- Parameters
node_name – The name of the node to delete.
- Raises
KeyError – Raised if the node does not exist in the graph.
- delete_node_if_exists(node_name: str) None[source]
Delete this node and all edges referencing it.
Ignores any node that is not in the graph, rather than throwing an exception.
- Parameters
node_name – The name of the node to delete.
- add_edge(ind_node: str, dep_node: str) None[source]
Add an edge (dependency) between the specified nodes.
- Parameters
ind_node – The independent node to add an edge to.
dep_node – The dependent node that has a dependency on the ind_node.
- Raises
KeyError – Either the ind_node, or dep_node do not exist.
DAGValidationError – Raised if the resulting graph is invalid.
- delete_edge(ind_node: str, dep_node: str) None[source]
Delete an edge from the graph.
- Parameters
ind_node – The independent node to delete an edge from.
dep_node – The dependent node that has a dependency on the ind_node.
- Raises
KeyError – Raised when the edge doesn’t already exist.
- transpose() runway.cfngin.dag.DAG[source]
Build a new graph with the edges reversed.
- walk(walk_func: Callable[[str], Any]) None[source]
Walk each node of the graph in reverse topological order.
This can be used to perform a set of operations, where the next operation depends on the previous operation. It’s important to note that walking happens serially, and is not parallelized.
- Parameters
walk_func – The function to be called on each node of the graph.
- transitive_reduction() None[source]
Perform a transitive reduction on the DAG.
The transitive reduction of a graph is a graph with as few edges as possible with the same reachability as the original graph.
- rename_edges(old_node_name: str, new_node_name: str) None[source]
Change references to a node in existing edges.
- Parameters
old_node_name – The old name for the node.
new_node_name – The new name for the node.
- predecessors(node: str) List[str][source]
Return a list of all immediate predecessors of the given node.
- Parameters
node (str) – The node whose predecessors you want to find.
- Returns
A list of nodes that are immediate predecessors to node.
- Return type
List[str]
- downstream(node: str) List[str][source]
Return a list of all nodes this node has edges towards.
- Parameters
node – The node whose downstream nodes you want to find.
- Returns
A list of nodes that are immediately downstream from the node.
- all_downstreams(node: str) List[str][source]
Return a list of all nodes downstream in topological order.
- Parameters
node – The node whose downstream nodes you want to find.
- Returns
A list of nodes that are downstream from the node.
- filter(nodes: List[str]) runway.cfngin.dag.DAG[source]
Return a new DAG with only the given nodes and their dependencies.
- Parameters
nodes – The nodes you are interested in.
- from_dict(graph_dict: Dict[str, Union[Iterable[str], Any]]) None[source]
Reset the graph and build it from the passed dictionary.
The dictionary takes the form of {node_name: [directed edges]}
- Parameters
graph_dict – The dictionary used to create the graph.
- Raises
TypeError – Raised if the value of items in the dict are not lists.
- topological_sort() List[str][source]
Return a topological ordering of the DAG.
- Raises
ValueError – Raised if the graph is not acyclic.
- __new__(**kwargs)
- runway.cfngin.dag.walk(dag: runway.cfngin.dag.DAG, walk_func: Callable[[str], Any]) None[source]
Walk a DAG.
- class runway.cfngin.dag.UnlimitedSemaphore[source]
Bases:
objectthreading.Semaphore, but acquire always succeeds.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.dag.ThreadedWalker[source]
Bases:
objectWalk a DAG as quickly as the graph topology allows, using threads.
- __init__(semaphore: Union[threading.Semaphore, UnlimitedSemaphore])[source]
Instantiate class.
- Parameters
semaphore – A semaphore object which can be used to control how many steps are executed in parallel.
- __new__(**kwargs)
Import modules.
Hooks for AWS Lambda.
- class runway.cfngin.hooks.awslambda.PythonFunction[source]
Bases:
runway.cfngin.hooks.awslambda.base_classes.AwsLambdaHook[runway.cfngin.hooks.awslambda.python_requirements._project.PythonProject]Hook for creating an AWS Lambda Function using Python runtime.
- BUILD_LAYER: ClassVar[bool] = False
Flag to denote that this hook creates a Lambda Function deployment package.
- __init__(context: runway.context.CfnginContext, **kwargs: Any) None[source]
Instantiate class.
- args: PythonHookArgs
Parsed hook arguments.
- property deployment_package: DeploymentPackage[PythonProject]
AWS Lambda deployment package.
- property project: runway.cfngin.hooks.awslambda.python_requirements._project.PythonProject
Project being deployed as an AWS Lambda Function.
- __new__(**kwargs)
- build_response(stage: Literal['deploy', 'destroy', 'plan']) Optional[BaseModel]
Build response object that will be returned by this hook.
- Parameters
stage – The current stage being executed by the hook.
- plan() AwsLambdaHookDeployResponseTypedDict
Run during the plan stage.
- ctx: CfnginContext
CFNgin context object.
- class runway.cfngin.hooks.awslambda.PythonLayer[source]
Bases:
runway.cfngin.hooks.awslambda._python_hooks.PythonFunctionHook for creating an AWS Lambda Layer using Python runtime.
- __init__(context: runway.context.CfnginContext, **kwargs: Any) None
Instantiate class.
- __new__(**kwargs)
- build_response(stage: Literal['deploy', 'destroy', 'plan']) Optional[BaseModel]
Build response object that will be returned by this hook.
- Parameters
stage – The current stage being executed by the hook.
- property deployment_package: DeploymentPackage[PythonProject]
AWS Lambda deployment package.
- plan() AwsLambdaHookDeployResponseTypedDict
Run during the plan stage.
- property project: runway.cfngin.hooks.awslambda.python_requirements._project.PythonProject
Project being deployed as an AWS Lambda Function.
- args: PythonHookArgs
Parsed hook arguments.
Data models.
Argument data models.
- class runway.cfngin.hooks.awslambda.models.args.DockerOptions[source]
Bases:
runway.utils.BaseModelDocker options.
- disabled: bool
Explicitly disable the use of docker (default
False).If not disabled and Docker is unreachable, the hook will result in an error.
Example
args: docker: disabled: true
- extra_files: List[str]
List of absolute file paths within the Docker container to copy into the deployment package.
Some Python packages require extra OS libraries (
*.so) files at runtime. These files need to be included in the deployment package for the Lambda Function to run. List the files here and the hook will handle copying them into the deployment package.The file name may end in a wildcard (
*) to accommodate.sofiles that end in an variable number (see example below).If the file does not exist, it will result in an error.
Example
args: docker: extra_files: - /usr/lib64/mysql/libmysqlclient.so.* - /usr/lib64/libxmlsec1-openssl.so
- file: Optional[pathlib.Path]
Dockerfile to use to build an image for use in this process.
This,
image, orruntimemust be provided. If not provided,imagewill be used.Example
args: docker: file: Dockerfile
- image: Optional[str]
Docker image to use. If the image does not exist locally, it will be pulled.
This,
file(takes precedence), orruntimemust be provided. If onlyruntimeis provided, it will be used to determine the appropriate image to use.Example
args: docker: image: public.ecr.aws/sam/build-python3.9:latest
- name: Optional[str]
When providing a Dockerfile, this will be the name applied to the resulting image. It is the equivalent to
namein thename:tagsyntax of thedocker build [--tag, -t]command option.If not provided, a default image name is used.
This field is ignore unless
fileis provided.Example
args: docker: file: Dockerfile name: ${namespace}.runway.awslambda
- pull: bool
Always download updates to the specified image before use. When building an image, the
FROMimage will be updated during the build process (defaultTrue).Example
args: docker: pull: false
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.cfngin.hooks.awslambda.models.args.AwsLambdaHookArgs[source]
Bases:
runway.cfngin.hooks.base.HookArgsBaseModelBase class for AWS Lambda hook arguments.
- bucket_name: str
Name of the S3 Bucket where deployment package is/will be stored. The Bucket must be in the same region the Lambda Function is being deployed in.
- cache_dir: Optional[pathlib.Path]
Explicitly define the directory location. Must be an absolute path or it will be relative to the CFNgin module directory.
- compatible_architectures: Optional[List[str]]
A list of compatible instruction set architectures. (https://docs.aws.amazon.com/lambda/latest/dg/foundation-arch.html)
Only used by Lambda Layers.
Example
args: compatible_architectures: - x86_64 - arm64
- compatible_runtimes: Optional[List[str]]
A list of compatible function runtimes. When provided, the
runtimebeing used to build the deployment package must be included in the list or an error will be raised.Only used by Lambda Layers.
Example
args: compatible_runtimes: - python3.9 - python3.10
- docker: runway.cfngin.hooks.awslambda.models.args.DockerOptions
Docker options.
- extend_gitignore: List[str]
gitignore rules that should be added to the rules already defined in a
.gitignorefile in the source code directory. This can be used with or without an existing file. Files that match a gitignore rule will not be included in the deployment package..git/&.gitignorewill always be added.Important
This only applies to files in the
source_codedirectory.Example
args: extend_gitignore: - cfngin.yml - poetry.lock - poetry.toml - pyproject.toml
- license: Optional[str]
The layer’s software license. Can be any of the following:
A SPDX license identifier (e.g.
Apache-2.0).The URL of a license hosted on the internet (e.g.
https://opensource.org/licenses/Apache-2.0).The full text of the license.
Only used by Lambda Layers.
Example
args: license: Apache-2.0
- object_prefix: Optional[str]
Prefix to add to the S3 Object key.
The object will always be prefixed with
awslambda/functions. If provided, the value will be added to the end of the static prefix (e.g.awslambda/<functions|layers>/<object_prefix>/<file name>).
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- classmethod update_forward_refs(**localns: Any) None
Try to update ForwardRefs on fields based on this Model, globalns and localns.
- runtime: Optional[str]
Runtime of the Lambda Function (https://docs.aws.amazon.com/lambda/latest/dg/lambda-runtimes.html).
This,
docker.file, ordocker.imagemust be provided. Ifdocker.disabled, this field is required.When provided, the runtime available on the build system (Docker container or localhost) will be checked against this value. If they do not match, an error will be raised.
If the defined or detected runtime ever changes so that it no longer matches the deployment package in S3, the deployment package in S3 will be deleted and a new one will be built and uploaded.
- slim: bool
Automatically remove information and caches from dependencies (default
True). This is done by applying gitignore rules to the dependencies. These rules vary by language/runtime.
- source_code: pathlib.Path
Path to the Lambda Function source code.
Example
args: source_code: ./my/package
- class runway.cfngin.hooks.awslambda.models.args.PythonHookArgs[source]
Bases:
runway.cfngin.hooks.awslambda.models.args.AwsLambdaHookArgsHook arguments for a Python AWS Lambda deployment package.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- classmethod update_forward_refs(**localns: Any) None
Try to update ForwardRefs on fields based on this Model, globalns and localns.
- bucket_name: str
Name of the S3 Bucket where deployment package is/will be stored. The Bucket must be in the same region the Lambda Function is being deployed in.
- cache_dir: Optional[pathlib.Path]
Explicitly define the directory location. Must be an absolute path or it will be relative to the CFNgin module directory.
- compatible_architectures: Optional[List[str]]
A list of compatible instruction set architectures. (https://docs.aws.amazon.com/lambda/latest/dg/foundation-arch.html)
Only used by Lambda Layers.
Example
args: compatible_architectures: - x86_64 - arm64
- compatible_runtimes: Optional[List[str]]
A list of compatible function runtimes. When provided, the
runtimebeing used to build the deployment package must be included in the list or an error will be raised.Only used by Lambda Layers.
Example
args: compatible_runtimes: - python3.9 - python3.10
- docker: runway.cfngin.hooks.awslambda.models.args.DockerOptions
Docker options.
- extend_gitignore: List[str]
gitignore rules that should be added to the rules already defined in a
.gitignorefile in the source code directory. This can be used with or without an existing file. Files that match a gitignore rule will not be included in the deployment package..git/&.gitignorewill always be added.Important
This only applies to files in the
source_codedirectory.Example
args: extend_gitignore: - cfngin.yml - poetry.lock - poetry.toml - pyproject.toml
- license: Optional[str]
The layer’s software license. Can be any of the following:
A SPDX license identifier (e.g.
Apache-2.0).The URL of a license hosted on the internet (e.g.
https://opensource.org/licenses/Apache-2.0).The full text of the license.
Only used by Lambda Layers.
Example
args: license: Apache-2.0
- object_prefix: Optional[str]
Prefix to add to the S3 Object key.
The object will always be prefixed with
awslambda/functions. If provided, the value will be added to the end of the static prefix (e.g.awslambda/<functions|layers>/<object_prefix>/<file name>).
- runtime: Optional[str]
Runtime of the Lambda Function (https://docs.aws.amazon.com/lambda/latest/dg/lambda-runtimes.html).
This,
docker.file, ordocker.imagemust be provided. Ifdocker.disabled, this field is required.When provided, the runtime available on the build system (Docker container or localhost) will be checked against this value. If they do not match, an error will be raised.
If the defined or detected runtime ever changes so that it no longer matches the deployment package in S3, the deployment package in S3 will be deleted and a new one will be built and uploaded.
- source_code: pathlib.Path
Path to the Lambda Function source code.
Example
args: source_code: ./my/package
- extend_pip_args: Optional[List[str]]
Additional arguments that should be passed to
pip install.Important
When providing this field, be careful not to duplicate any of the arguments passed by this hook (e.g.
--requirements,--target,--no-input). Providing duplicate arguments will result in an error.Example
args: extend_pip_args: - '--proxy' - '[user:passwd@]proxy.server:port'
- slim: bool
Automatically remove information and caches from dependencies (default
True). This is done by applying the following gitignore rules to the dependencies:**/*.dist-info***/*.py[c|d|i|o]**/*.so**/__pycache__*
Response data models.
- class runway.cfngin.hooks.awslambda.models.responses.AwsLambdaHookDeployResponse[source]
Bases:
runway.utils.BaseModelData model for AwsLambdaHook deploy response.
When returned by the hook as
hook_data, this model is dumped to a standardDictusing the field’s aliases as thekeyin place of the attribute names. This is done so that thekeyis a direct match to a CloudFormation Property where the value should be used.- code_sha256: str
SHA256 of the deployment package. This can be used by CloudFormation as the value of
AWS::Lambda::Version.CodeSha256. (aliasCodeSha256)
- compatible_architectures: Optional[List[str]]
A list of compatible instruction set architectures. (https://docs.aws.amazon.com/lambda/latest/dg/foundation-arch.html) (alias
CompatibleArchitectures)
- compatible_runtimes: Optional[List[str]]
A list of compatible function runtimes. Used for filtering with
ListLayersandListLayerVersions. (aliasCompatibleRuntimes)
- license: Optional[str]
The layer’s software license (alias
License). Can be any of the following:A SPDX license identifier (e.g.
MIT).The URL of a license hosted on the internet (e.g.
https://opensource.org/licenses/MIT).The full text of the license.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- classmethod update_forward_refs(**localns: Any) None
Try to update ForwardRefs on fields based on this Model, globalns and localns.
Handle python requirements.
- class runway.cfngin.hooks.awslambda.python_requirements.PythonDeploymentPackage[source]
Bases:
runway.cfngin.hooks.awslambda.deployment_package.DeploymentPackage[PythonProject]AWS Lambda Python Deployment Package.
- property gitignore_filter: Optional[igittigitt.igittigitt.IgnoreParser]
Filter to use when zipping dependencies.
This should be overridden by subclasses if a filter should be used.
- static insert_layer_dir(file_path: pathlib.Path, relative_to: pathlib.Path) pathlib.Path[source]
Insert
pythondirectory into local file path for layer archive.- Parameters
file_path – Path to local file.
relative_to – Path to a directory that the file_path will be relative to in the deployment package.
- __init__(project: runway.cfngin.hooks.awslambda.deployment_package._ProjectTypeVar, usage_type: typing_extensions.Literal[function, layer] = 'function') None
Instantiate class.
The provided
.init()class method should be used in place of direct instantiation.- Parameters
project – Project that is being built into a deployment package.
usage_type – How the deployment package can be used by AWS Lambda.
- __new__(**kwargs)
- property archive_file: Path
Path to archive file.
Because the archive file path contains runtime, it’s use can cause a race condition or recursion error if used in some locations. If we removed runtime from the path we would not have a way to track changes to runtime which is more important than needing to be mindful of where this is used.
- property bucket: runway.core.providers.aws.s3._bucket.Bucket
AWS S3 bucket where deployment package will be uploaded.
- build() Path
Build the deployment package.
- build_tag_set(*, url_encoded: bool = True) Union[Dict[str, str], str]
Build tag set to be applied to the S3 object.
- Parameters
layer – Tag the deployment package as a Lambda Layer or not.
url_encoded – Whether to return a dict or URL encoded query string.
- property code_sha256: str
SHA256 of the archive file.
- Returns
Value to pass to CloudFormation
AWS::Lambda::Version.CodeSha256.- Raises
FileNotFoundError – Property accessed before archive file has been built.
- property compatible_architectures: Optional[List[str]]
List of compatible instruction set architectures.
- classmethod init(project: runway.cfngin.hooks.awslambda.deployment_package._ProjectTypeVar, usage_type: typing_extensions.Literal[function, layer] = 'function') runway.cfngin.hooks.awslambda.deployment_package.DeploymentPackage[runway.cfngin.hooks.awslambda.deployment_package._ProjectTypeVar]
Initialize deployment package.
This should be used in place of creating an instance of this class directly as it will automatically account for the S3 object already existing.
- Parameters
project – Project that is being built into a deployment package.
usage_type – How the deployment package can be used by AWS Lambda.
- Returns
Instance of generic S3 object class if S3 object exists else an instance of this class.
- iterate_dependency_directory() Iterator[Path]
Iterate over the contents of the dependency directory.
If
gitignore_filteris set, it will be used to exclude files.
- property md5_checksum: str
MD5 of the archive file.
- Returns
Value to pass as ContentMD5 when uploading to AWS S3.
- Raises
FileNotFoundError – Property accessed before archive file has been built.
- property object_version_id: Optional[str]
S3 object version ID.
- Returns
The ID of the current object version. This will only have a value if versioning is enabled on the bucket.
- upload(*, build: bool = True) None
Upload deployment package.
- Parameters
build – If true, the deployment package will be built before before trying to upload it. If false, it must have already been built.
- usage_type: Literal['function', 'layer']
How the deployment package can be used by AWS Lambda.
- class runway.cfngin.hooks.awslambda.python_requirements.PythonDockerDependencyInstaller[source]
Bases:
runway.cfngin.hooks.awslambda.docker.DockerDependencyInstallerDocker dependency installer for Python.
- __init__(project: PythonProject, *, client: Optional[DockerClient] = None, context: Optional[Union[CfnginContext, RunwayContext]] = None) None[source]
Instantiate class.
- Parameters
project – awslambda project.
client – Pre-configured
docker.client.DockerClient.context – CFNgin or Runway context object.
- property bind_mounts: List[docker.types.services.Mount]
Bind mounts that will be used by the container.
- property environment_variables: Dict[str, str]
Environment variables to pass to the docker container.
This is a subset of the environment variables stored in the context object as some will cause issues if they are passed.
- property python_version: Optional[runway.utils._version.Version]
Version of Python installed in the docker container.
- property runtime: Optional[str]
AWS Lambda runtime determined from the docker container’s Python version.
- __new__(**kwargs)
- build_image(docker_file: Path, *, name: Optional[str] = None, tag: Optional[str] = None) Image
Build Docker image from Dockerfile.
This method is exposed as a low-level interface.
imageshould be used in place for this for most cases.- Parameters
docker_file – Path to the Dockerfile to build. This path should be absolute, must exist, and must be a file.
name – Name of the Docker image. The name should not contain a tag. If not provided, a default value is use.
tag – Tag to apply to the image after it is built. If not provided, a default value of
latestis used.
- Returns
Object representing the image that was built.
- classmethod from_project(project: Project[AwsLambdaHookArgs]) Optional[_T]
Instantiate class from a project.
High-level method that wraps instantiation in error handling.
- Parameters
project – Project being processed.
- Returns
Object to handle dependency installation with Docker if Docker is available and not disabled.
- Raises
DockerConnectionRefused – Docker is not install or is unreachable.
- property image: Union[docker.models.images.Image, str]
Docker image that will be used.
- Raises
ValueError – Insufficient data to determine the desired Docker image.
- install() None
Install dependencies using Docker.
Commands are run as they are defined in the following cached properties:
- log_docker_msg_bytes(stream: Iterator[bytes], *, level: int = 20) List[str]
Log Docker output message from blocking generator that return bytes.
- Parameters
stream – Blocking generator that returns log messages as bytes.
level – Log level to use when logging messages.
- Returns
List of log messages.
- log_docker_msg_dict(stream: Iterator[Dict[str, Any]], *, level: int = 20) List[str]
Log Docker output message from blocking generator that return dict.
- Parameters
stream – Blocking generator that returns log messages as a dict.
level – Log level to use when logging messages.
- Returns
list of log messages.
- pull_image(name: str, *, force: bool = True) docker.models.images.Image
Pull a Docker image from a repository if it does not exist locally.
This method is exposed as a low-level interface.
imageshould be used in place for this for most cases.- Parameters
name – Name of the Docker image including tag.
force – Always pull the image even if it exists locally. This will ensure that the latest version is always used.
- Returns
Object representing the image found locally or pulled from a repository.
- run_command(command: str, *, level: int = 20) List[str]
Execute equivalent of
docker container run.- Parameters
command – Command to be run.
level – Log level to use when logging messages.
- Raises
DockerExecFailedError – Docker container returned a non-zero exit code.
- Returns
List of log messages.
- client: DockerClient
Docker client.
- ctx: Union[CfnginContext, RunwayContext]
Context object.
- options: DockerOptions
Hook arguments specific to Docker.
- class runway.cfngin.hooks.awslambda.python_requirements.PythonProject[source]
Bases:
runway.cfngin.hooks.awslambda.base_classes.Project[runway.cfngin.hooks.awslambda.models.args.PythonHookArgs]Python project.
- property docker: Optional[runway.cfngin.hooks.awslambda.python_requirements._docker.PythonDockerDependencyInstaller]
Docker interface that can be used to build the project.
- property metadata_files: Tuple[Path, ...]
Project metadata files.
Files are only included in return value if they exist.
- property runtime: str
Runtime of the build system.
Value should be a valid Lambda Function runtime (https://docs.aws.amazon.com/lambda/latest/dg/lambda-runtimes.html).
- property pip: runway.dependency_managers._pip.Pip
Pip dependency manager.
- property pipenv: Optional[runway.dependency_managers._pipenv.Pipenv]
Pipenv dependency manager.
- Returns
If the project uses pipenv and pipenv is not explicitly disabled, an object for interfacing with pipenv will be returned.
- Raises
PipenvNotFoundError – pipenv is not installed or not found in PATH.
- property poetry: Optional[runway.dependency_managers._poetry.Poetry]
Poetry dependency manager.
- Returns
If the project uses poetry and poetry is not explicitly disabled, an object for interfacing with poetry will be returned.
- Raises
PoetryNotFound – poetry is not installed or not found in PATH.
- property project_type: typing_extensions.Literal[pip, pipenv, poetry]
Type of python project.
- property requirements_txt: Optional[Path]
Dependency file for the project.
- property supported_metadata_files: Set[str]
Names of all supported metadata files.
- Returns
Set of file names - not paths.
- property tmp_requirements_txt: Path
Temporary requirements.txt file.
This path is only used when exporting from another format.
- __init__(args: runway.cfngin.hooks.awslambda.base_classes._AwsLambdaHookArgsTypeVar_co, context: runway.context.CfnginContext) None
Instantiate class.
- Parameters
args – Parsed hook arguments.
context – Context object.
- __new__(**kwargs)
- property build_directory: pathlib.Path
Directory being used to build deployment package.
- property cache_dir: Optional[pathlib.Path]
Directory where a dependency manager’s cache data will be stored.
- Returns
Explicit cache directory if provided or default cache directory if it is not provided. If configured to not use cache, will always be
None.
- cleanup_on_error() None
Cleanup project files when an error occurs.
This will be run before
self.cleanup()if an error has occurred.Hooks should call this method in an
exceptblock and reraise the error afterward.
- property compatible_architectures: Optional[List[str]]
List of compatible instruction set architectures.
- property compatible_runtimes: Optional[List[str]]
List of compatible runtimes.
Value should be valid Lambda Function runtimes (https://docs.aws.amazon.com/lambda/latest/dg/lambda-runtimes.html).
- Raises
ValueError – Defined or detected runtime is not in the list of compatible runtimes.
- property dependency_directory: pathlib.Path
Directory to use as the target of
pip install --target.
- property license: Optional[str]
Software license for the project.
Can be any of the following:
A SPDX license identifier (e.g.
MIT).The URL of a license hosted on the internet (e.g.
https://opensource.org/licenses/MIT).The full text of the license.
- property project_root: pathlib.Path
Root directory of the project.
The top-level directory containing the source code and all configuration/metadata files (e.g. pyproject.toml, package.json).
The project root can be different from the source code directory but, if they are different, the project root should contain the source code directory. If it does not, the source code directory will be always be used.
The primary use case for this property is to allow configuration files to exist outside of the source code directory. The
project_typecan and should rely on the value of this property when determining the type.
- property source_code: runway.cfngin.hooks.awslambda.source_code.SourceCode
Project source code.
Lazy load source code object. Extends gitignore as needed.
- args: _AwsLambdaHookArgsTypeVar_co
Parsed hook arguments.
- ctx: CfnginContext
CFNgin context object.
Base classes.
- class runway.cfngin.hooks.awslambda.base_classes.Project[source]
Bases:
Generic[runway.cfngin.hooks.awslambda.base_classes._AwsLambdaHookArgsTypeVar_co]Project containing source code for an AWS Lambda Function.
- __init__(args: runway.cfngin.hooks.awslambda.base_classes._AwsLambdaHookArgsTypeVar_co, context: runway.context.CfnginContext) None[source]
Instantiate class.
- Parameters
args – Parsed hook arguments.
context – Context object.
- args: _AwsLambdaHookArgsTypeVar_co
Parsed hook arguments.
- ctx: CfnginContext
CFNgin context object.
- property build_directory: pathlib.Path
Directory being used to build deployment package.
- property cache_dir: Optional[pathlib.Path]
Directory where a dependency manager’s cache data will be stored.
- Returns
Explicit cache directory if provided or default cache directory if it is not provided. If configured to not use cache, will always be
None.
- property compatible_architectures: Optional[List[str]]
List of compatible instruction set architectures.
- property compatible_runtimes: Optional[List[str]]
List of compatible runtimes.
Value should be valid Lambda Function runtimes (https://docs.aws.amazon.com/lambda/latest/dg/lambda-runtimes.html).
- Raises
ValueError – Defined or detected runtime is not in the list of compatible runtimes.
- property dependency_directory: pathlib.Path
Directory to use as the target of
pip install --target.
- property license: Optional[str]
Software license for the project.
Can be any of the following:
A SPDX license identifier (e.g.
MIT).The URL of a license hosted on the internet (e.g.
https://opensource.org/licenses/MIT).The full text of the license.
- property metadata_files: Tuple[pathlib.Path, ...]
Project metadata files (e.g.
project.json,pyproject.toml).
- property runtime: str
runtime of the build system.
Value should be a valid Lambda Function runtime (https://docs.aws.amazon.com/lambda/latest/dg/lambda-runtimes.html).
This property can be overwritten by subclasses when runtime can be determined through additional means.
- property source_code: runway.cfngin.hooks.awslambda.source_code.SourceCode
Project source code.
Lazy load source code object. Extends gitignore as needed.
- property project_root: pathlib.Path
Root directory of the project.
The top-level directory containing the source code and all configuration/metadata files (e.g. pyproject.toml, package.json).
The project root can be different from the source code directory but, if they are different, the project root should contain the source code directory. If it does not, the source code directory will be always be used.
The primary use case for this property is to allow configuration files to exist outside of the source code directory. The
project_typecan and should rely on the value of this property when determining the type.
- property project_type: str
Type of project (e.g. poetry, yarn).
This should be considered more of a “subtype” as the subclass should distinguish project language. The value of this property should reflect the project/dependency management tool used within the project.
The value of this property should be calculated without initializing other properties (e.g.
source_code) except forproject_rootso that it can be used in their initialization process.
- property supported_metadata_files: Set[str]
Names of all supported metadata files.
- Returns
Set of file names - not paths.
- cleanup() None[source]
Cleanup project files at the end of execution.
If any cleanup is needed (e.g. removal of temporary dependency directory) it should be implimented here. Hook’s should call this method in a
finallyblock to ensure it is run even if the rest of the hook encountered an error.
- cleanup_on_error() None[source]
Cleanup project files when an error occurs.
This will be run before
self.cleanup()if an error has occurred.Hooks should call this method in an
exceptblock and reraise the error afterward.
- install_dependencies() None[source]
Install project dependencies.
Arguments/options should be read from the
argsattribute of this object instead of being passed into the method call. The method itself only exists for timing and filling in custom handling that is required for each project type.
- __new__(**kwargs)
- class runway.cfngin.hooks.awslambda.base_classes.AwsLambdaHook[source]
Bases:
runway.cfngin.hooks.protocols.CfnginHookProtocol,Generic[runway.cfngin.hooks.awslambda.base_classes._ProjectTypeVar]Base class for AWS Lambda hooks.
- BUILD_LAYER: ClassVar[bool] = False
Flag to denote if the hook creates a Lambda Function or Layer deployment package.
- args: AwsLambdaHookArgs
Parsed hook arguments.
- __init__(context: runway.context.CfnginContext, **_kwargs: Any) None[source]
Instantiate class.
This method should be overridden by subclasses. This is required to set the value of the args attribute.
- Parameters
context – CFNgin context object (passed in by CFNgin).
- ctx: CfnginContext
CFNgin context object.
- property deployment_package: DeploymentPackage[_ProjectTypeVar]
AWS Lambda deployment package.
- property project: runway.cfngin.hooks.awslambda.base_classes._ProjectTypeVar
Project being deployed as an AWS Lambda Function.
- __new__(**kwargs)
- build_response(stage: typing_extensions.Literal[deploy]) runway.cfngin.hooks.awslambda.models.responses.AwsLambdaHookDeployResponse[source]
- build_response(stage: typing_extensions.Literal[destroy]) Optional[BaseModel]
- build_response(stage: typing_extensions.Literal[plan]) runway.cfngin.hooks.awslambda.models.responses.AwsLambdaHookDeployResponse
Build response object that will be returned by this hook.
- Parameters
stage – The current stage being executed by the hook.
- cleanup() None[source]
Cleanup temporary files at the end of execution.
If any cleanup is needed (e.g. removal of temporary dependency directory) it should be implimented here. A Hook’s stage methods should call this method in a
finallyblock to ensure it is run even if the rest of the hook encountered an error.Example
def pre_deploy(self) -> Any: try: pass # primary logic except BaseException: self.cleanup_on_error() raise finally: self.cleanup()
- cleanup_on_error() None[source]
Cleanup temporary files when an error occurs.
This will be run before
self.cleanup()if an error has occurred.A Hook’s stage method should call this method in an
exceptblock and reraise the error afterward.Example
def pre_deploy(self) -> Any: try: pass # primary logic except BaseException: self.cleanup_on_error() raise finally: self.cleanup()
- plan() AwsLambdaHookDeployResponseTypedDict[source]
Run during the plan stage.
Constant values.
- runway.cfngin.hooks.awslambda.constants.AWS_SAM_BUILD_IMAGE_PREFIX = 'public.ecr.aws/sam/build-'
Prefix for build image registries.
- runway.cfngin.hooks.awslambda.constants.DEFAULT_IMAGE_NAME = 'runway.cfngin.hooks.awslambda'
Default name to apply to an image when building from a Dockerfile.
- runway.cfngin.hooks.awslambda.constants.DEFAULT_IMAGE_TAG = 'latest'
Default tag to apply to an image when building from a Dockerfile.
Deployment package.
- class runway.cfngin.hooks.awslambda.deployment_package.DeploymentPackage[source]
Bases:
runway.mixins.DelCachedPropMixin,Generic[runway.cfngin.hooks.awslambda.deployment_package._ProjectTypeVar]AWS Lambda Deployment Package.
When interacting with subclass of this instance, it is recommended to only call the methods defined within this parent class. This ensures compatibility with the S3 object class that can be returned.
- META_TAGS: ClassVar[Dict[str, str]] = {'code_sha256': 'runway.cfngin:awslambda.code_sha256', 'compatible_architectures': 'runway.cfngin:awslambda.compatible_architectures', 'compatible_runtimes': 'runway.cfngin:awslambda.compatible_runtimes', 'license': 'runway.cfngin:awslambda.license', 'md5_checksum': 'runway.cfngin:awslambda.md5_checksum', 'runtime': 'runway.cfngin:awslambda.runtime', 'source_code.hash': 'runway.cfngin:awslambda.source_code.hash'}
Mapping of metadata to the tag-key is is stored in on the S3 object.
- SIZE_EOCD: Final[Literal[22]] = 22
Size of a zip file’s End of Central Directory Record (empty zip).
- ZIPFILE_PERMISSION_MASK: ClassVar[int] = 33488896
Mask to retrieve unix file permissions from the external attributes property of a
zipfile.ZipInfo.
- __init__(project: runway.cfngin.hooks.awslambda.deployment_package._ProjectTypeVar, usage_type: typing_extensions.Literal[function, layer] = 'function') None[source]
Instantiate class.
The provided
.init()class method should be used in place of direct instantiation.- Parameters
project – Project that is being built into a deployment package.
usage_type – How the deployment package can be used by AWS Lambda.
- project: _ProjectTypeVar
Project that is being built into a deployment package.
- usage_type: Literal['function', 'layer']
How the deployment package can be used by AWS Lambda.
- property archive_file: Path
Path to archive file.
Because the archive file path contains runtime, it’s use can cause a race condition or recursion error if used in some locations. If we removed runtime from the path we would not have a way to track changes to runtime which is more important than needing to be mindful of where this is used.
- property bucket: runway.core.providers.aws.s3._bucket.Bucket
AWS S3 bucket where deployment package will be uploaded.
- property code_sha256: str
SHA256 of the archive file.
- Returns
Value to pass to CloudFormation
AWS::Lambda::Version.CodeSha256.- Raises
FileNotFoundError – Property accessed before archive file has been built.
- property compatible_architectures: Optional[List[str]]
List of compatible instruction set architectures.
- property gitignore_filter: Optional[igittigitt.IgnoreParser]
Filter to use when zipping dependencies.
This should be overridden by subclasses if a filter should be used.
- property md5_checksum: str
MD5 of the archive file.
- Returns
Value to pass as ContentMD5 when uploading to AWS S3.
- Raises
FileNotFoundError – Property accessed before archive file has been built.
- property object_version_id: Optional[str]
S3 object version ID.
- Returns
The ID of the current object version. This will only have a value if versioning is enabled on the bucket.
- build_tag_set(*, url_encoded: typing_extensions.Literal[True] = True) str[source]
- build_tag_set(*, url_encoded: typing_extensions.Literal[False] = True) Dict[str, str]
- build_tag_set(*, url_encoded: bool = True) Union[Dict[str, str], str]
Build tag set to be applied to the S3 object.
- Parameters
layer – Tag the deployment package as a Lambda Layer or not.
url_encoded – Whether to return a dict or URL encoded query string.
- static insert_layer_dir(file_path: Path, relative_to: Path) Path[source]
Insert directory into local file path for layer archive.
If required, this should be overridden by a subclass for language specific requirements.
- Parameters
file_path – Path to local file.
relative_to – Path to a directory that the file_path will be relative to in the deployment package.
- iterate_dependency_directory() Iterator[Path][source]
Iterate over the contents of the dependency directory.
If
gitignore_filteris set, it will be used to exclude files.
- upload(*, build: bool = True) None[source]
Upload deployment package.
- Parameters
build – If true, the deployment package will be built before before trying to upload it. If false, it must have already been built.
- classmethod init(project: runway.cfngin.hooks.awslambda.deployment_package._ProjectTypeVar, usage_type: typing_extensions.Literal[function, layer] = 'function') runway.cfngin.hooks.awslambda.deployment_package.DeploymentPackage[runway.cfngin.hooks.awslambda.deployment_package._ProjectTypeVar][source]
Initialize deployment package.
This should be used in place of creating an instance of this class directly as it will automatically account for the S3 object already existing.
- Parameters
project – Project that is being built into a deployment package.
usage_type – How the deployment package can be used by AWS Lambda.
- Returns
Instance of generic S3 object class if S3 object exists else an instance of this class.
- __new__(**kwargs)
- class runway.cfngin.hooks.awslambda.deployment_package.DeploymentPackageS3Object[source]
Bases:
runway.cfngin.hooks.awslambda.deployment_package.DeploymentPackage[runway.cfngin.hooks.awslambda.deployment_package._ProjectTypeVar]AWS Lambda Deployment Package.
This should not need to be subclassed as the interactions required should be universal.
- project
Project that is being built into a deployment package.
- Type
_ProjectTypeVar
- property code_sha256: str
SHA256 of the archive file.
- Returns
Value to pass to CloudFormation
AWS::Lambda::Version.CodeSha256.- Raises
RequiredTagNotFound – A required tag was not found.
- property compatible_architectures: Optional[List[str]]
List of compatible instruction set architectures.
- __init__(project: runway.cfngin.hooks.awslambda.deployment_package._ProjectTypeVar, usage_type: typing_extensions.Literal[function, layer] = 'function') None
Instantiate class.
The provided
.init()class method should be used in place of direct instantiation.- Parameters
project – Project that is being built into a deployment package.
usage_type – How the deployment package can be used by AWS Lambda.
- __new__(**kwargs)
- property archive_file: Path
Path to archive file.
Because the archive file path contains runtime, it’s use can cause a race condition or recursion error if used in some locations. If we removed runtime from the path we would not have a way to track changes to runtime which is more important than needing to be mindful of where this is used.
- property bucket: runway.core.providers.aws.s3._bucket.Bucket
AWS S3 bucket where deployment package will be uploaded.
- build_tag_set(*, url_encoded: bool = True) Union[Dict[str, str], str]
Build tag set to be applied to the S3 object.
- Parameters
layer – Tag the deployment package as a Lambda Layer or not.
url_encoded – Whether to return a dict or URL encoded query string.
- property gitignore_filter: Optional[igittigitt.IgnoreParser]
Filter to use when zipping dependencies.
This should be overridden by subclasses if a filter should be used.
- property head: Optional[HeadObjectOutputTypeDef]
Response from HeadObject API call.
- classmethod init(project: runway.cfngin.hooks.awslambda.deployment_package._ProjectTypeVar, usage_type: typing_extensions.Literal[function, layer] = 'function') runway.cfngin.hooks.awslambda.deployment_package.DeploymentPackage[runway.cfngin.hooks.awslambda.deployment_package._ProjectTypeVar]
Initialize deployment package.
This should be used in place of creating an instance of this class directly as it will automatically account for the S3 object already existing.
- Parameters
project – Project that is being built into a deployment package.
usage_type – How the deployment package can be used by AWS Lambda.
- Returns
Instance of generic S3 object class if S3 object exists else an instance of this class.
- static insert_layer_dir(file_path: Path, relative_to: Path) Path
Insert directory into local file path for layer archive.
If required, this should be overridden by a subclass for language specific requirements.
- Parameters
file_path – Path to local file.
relative_to – Path to a directory that the file_path will be relative to in the deployment package.
- iterate_dependency_directory() Iterator[Path]
Iterate over the contents of the dependency directory.
If
gitignore_filteris set, it will be used to exclude files.
- property md5_checksum: str
MD5 of the archive file.
- Returns
Value to pass as ContentMD5 when uploading to AWS S3.
- Raises
RequiredTagNotFoundError – A required tag was not found.
- property object_version_id: Optional[str]
S3 object version ID.
- Returns
The ID of the current object version. This will only have a value if versioning is enabled on the bucket.
- property runtime: str
Runtime of the deployment package.
- Raises
RequiredTagNotFoundError – A required tag was not found.
- build() Path[source]
Build the deployment package.
The object should already exist. This method only exists as a “placeholder” to match the parent class. If the object does not already exist, and error is raised.
- Raises
S3ObjectDoesNotExistError – The S3 object does not exist.
- upload(*, build: bool = True) None[source]
Upload deployment package.
The object should already exist. This method only exists as a “placeholder” to match the parent class. If the object does not already exist, and error is raised.
- Parameters
build – If true, the deployment package will be built before before trying to upload it. If false, it must have already been built.
- Raises
S3ObjectDoesNotExistError – The S3 object does not exist.
Docker logic for the awslambda hook.
- class runway.cfngin.hooks.awslambda.docker.DockerDependencyInstaller[source]
Bases:
objectDocker dependency installer.
- CACHE_DIR: ClassVar[str] = '/var/task/cache_dir'
Mount path where dependency managers can cache data.
- DEPENDENCY_DIR: ClassVar[str] = '/var/task/lambda'
Mount path were dependencies will be installed to within the Docker container. Other files can be moved to this directory to be included in the deployment package.
- PROJECT_DIR: ClassVar[str] = '/var/task/project'
Mount path where the project directory is available within the Docker container.
- __init__(project: Project[AwsLambdaHookArgs], *, client: Optional[DockerClient] = None, context: Optional[Union[CfnginContext, RunwayContext]] = None) None[source]
Instantiate class.
This is a low-level method that requires the user to implement error handling. It is recommended to use
from_project()instead of instantiating this class directly.- Parameters
project – awslambda project.
client – Pre-configured
docker.client.DockerClient.context – CFNgin or Runway context object.
- client: DockerClient
Docker client.
- ctx: Union[CfnginContext, RunwayContext]
Context object.
- options: DockerOptions
Hook arguments specific to Docker.
- property bind_mounts: List[docker.types.services.Mount]
Bind mounts that will be used by the container.
- property environment_variables: Dict[str, str]
Environment variables to pass to the Docker container.
This is a subset of the environment variables stored in the context object as some will cause issues if they are passed.
- property image: Union[docker.models.images.Image, str]
Docker image that will be used.
- Raises
ValueError – Insufficient data to determine the desired Docker image.
- __new__(**kwargs)
- build_image(docker_file: Path, *, name: Optional[str] = None, tag: Optional[str] = None) Image[source]
Build Docker image from Dockerfile.
This method is exposed as a low-level interface.
imageshould be used in place for this for most cases.- Parameters
docker_file – Path to the Dockerfile to build. This path should be absolute, must exist, and must be a file.
name – Name of the Docker image. The name should not contain a tag. If not provided, a default value is use.
tag – Tag to apply to the image after it is built. If not provided, a default value of
latestis used.
- Returns
Object representing the image that was built.
- log_docker_msg_bytes(stream: Iterator[bytes], *, level: int = 20) List[str][source]
Log Docker output message from blocking generator that return bytes.
- Parameters
stream – Blocking generator that returns log messages as bytes.
level – Log level to use when logging messages.
- Returns
List of log messages.
- log_docker_msg_dict(stream: Iterator[Dict[str, Any]], *, level: int = 20) List[str][source]
Log Docker output message from blocking generator that return dict.
- Parameters
stream – Blocking generator that returns log messages as a dict.
level – Log level to use when logging messages.
- Returns
list of log messages.
- install() None[source]
Install dependencies using Docker.
Commands are run as they are defined in the following cached properties:
- pull_image(name: str, *, force: bool = True) docker.models.images.Image[source]
Pull a Docker image from a repository if it does not exist locally.
This method is exposed as a low-level interface.
imageshould be used in place for this for most cases.- Parameters
name – Name of the Docker image including tag.
force – Always pull the image even if it exists locally. This will ensure that the latest version is always used.
- Returns
Object representing the image found locally or pulled from a repository.
- run_command(command: str, *, level: int = 20) List[str][source]
Execute equivalent of
docker container run.- Parameters
command – Command to be run.
level – Log level to use when logging messages.
- Raises
DockerExecFailedError – Docker container returned a non-zero exit code.
- Returns
List of log messages.
- classmethod from_project(project: Project[AwsLambdaHookArgs]) Optional[_T][source]
Instantiate class from a project.
High-level method that wraps instantiation in error handling.
- Parameters
project – Project being processed.
- Returns
Object to handle dependency installation with Docker if Docker is available and not disabled.
- Raises
DockerConnectionRefused – Docker is not install or is unreachable.
Exceptions for awslambda hooks.
- exception runway.cfngin.hooks.awslambda.exceptions.DeploymentPackageEmptyError[source]
Bases:
runway.cfngin.exceptions.CfnginErrorDeployment package is empty.
This can be caused by an incorrect source code directory or a gitignore rule unintentionally ignoring all source code.
Any empty deployment package is determined by checking the size of the archive file. If the size is <=22 (the size a zip file End of Central Directory Record) it has no contents.
- __init__(archive_file: Path) None[source]
Instantiate class.
- Parameters
archive_file – The empty archive file.
- archive_file: Path
The deployment package archive file.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.hooks.awslambda.exceptions.RuntimeMismatchError[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRequired runtime does not match the detected runtime.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
Source code.
- class runway.cfngin.hooks.awslambda.source_code.SourceCode[source]
Bases:
objectSource code iterable.
- __init__(root_directory: StrPath, *, gitignore_filter: Optional[igittigitt.IgnoreParser] = None, include_files_in_hash: Optional[Sequence[Path]] = None, project_root: Optional[StrPath] = None) None[source]
Instantiate class.
- Parameters
root_directory – The root directory containing the source code.
gitignore_filter – Object that has been pre-populated with rules/patterns to determine if a file should be ignored.
include_files_in_hash – Files that should be included in hash calculation even if they are filtered by gitignore (e.g.
poetry.lock).project_root – Optional project root if the source code is located within a larger project. This should only be used if the contents of value of
include_files_in_hashcontains paths that exist outside of the root directory. If this is provided, it must be a parent of the root directory.
- gitignore_filter: igittigitt.igittigitt.IgnoreParser
Filter to use when zipping dependencies. If file/folder matches the filter, it should be ignored.
- root_directory: pathlib.Path
The root directory containing the source code.
- project_root: pathlib.Path
Top-level directory containing the project metadata files and source code root directory. The value can be the same as
root_directory. If it is not, it must be a parent ofroot_directory.
- property md5_hash: str
Calculate the md5 hash of the directory contents.
This can be resource intensive depending on the size of the project.
- add_filter_rule(pattern: str) None[source]
Add rule to ignore filter.
- Parameters
pattern – The gitignore pattern to add to the filter.
- __new__(**kwargs)
- sorted(*, reverse: bool = False) List[pathlib.Path][source]
Sorted list of source code files.
- Parameters
reverse – Sort the list in reverse.
- Returns
Sorted list of source code files excluding those that match the ignore filter.
- __iter__() Iterator[pathlib.Path][source]
Iterate over the source code files.
- Yields
Files that do not match the ignore filter. Order in arbitrary.
Type definitions.
Docker hook.
- class runway.cfngin.hooks.docker.LoginArgs[source]
Bases:
runway.utils.BaseModelArgs passed to the docker.login hook.
- ecr: Optional[ElasticContainerRegistry]
Information describing an ECR registry.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- runway.cfngin.hooks.docker.login(*, context: runway.context.CfnginContext, **kwargs: Any) runway.cfngin.hooks.docker.hook_data.DockerHookData[source]
Docker login hook.
Replicates the functionality of
docker logincli command.kwargs are parsed by
LoginArgs.
Docker image actions & argument parsers.
Replicates the functionality of docker image CLI commands.
- class runway.cfngin.hooks.docker.image.DockerImageBuildApiOptions[source]
Bases:
runway.utils.BaseModelOptions for controlling Docker.
- extra_hosts: Dict[str, str]
Extra hosts to add to /etc/hosts in the build containers. Defined as a mapping of hostname to IP address.
- platform: Optional[str]
Set platform if server is multi-platform capable. Uses format
os[/arch[/variant]].
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.cfngin.hooks.docker.image.ImageBuildArgs[source]
Bases:
runway.utils.BaseModelArgs passed to image.build.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- classmethod update_forward_refs(**localns: Any) None
Try to update ForwardRefs on fields based on this Model, globalns and localns.
- ecr_repo: Optional[ElasticContainerRegistryRepository]
AWS Elastic Container Registry repository information. Providing this will automatically construct the repo URI. If provided, do not provide
repo.If using a private registry, only
repo_nameis required. If using a public registry,repo_nameandregistry_alias.
- path: DirectoryPath
Path to the directory containing the Dockerfile.
- docker: DockerImageBuildApiOptions
Options for
docker image build.
- class runway.cfngin.hooks.docker.image.ImagePushArgs[source]
Bases:
runway.utils.BaseModelArgs passed to image.push.
- ecr_repo: Optional[ElasticContainerRegistryRepository]
AWS Elastic Container Registry repository information. Providing this will automatically construct the repo URI. If provided, do not provide
repo.If using a private registry, only
repo_nameis required. If using a public registry,repo_nameandregistry_alias.
- image: Optional[DockerImage]
Image to push.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.cfngin.hooks.docker.image.ImageRemoveArgs[source]
Bases:
runway.utils.BaseModelArgs passed to image.remove.
- ecr_repo: Optional[ElasticContainerRegistryRepository]
AWS Elastic Container Registry repository information. Providing this will automatically construct the repo URI. If provided, do not provide
repo.If using a private registry, only
repo_nameis required. If using a public registry,repo_nameandregistry_alias.
- image: Optional[DockerImage]
Image to push.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- runway.cfngin.hooks.docker.image.build(*, context: runway.context.CfnginContext, **kwargs: Any) runway.cfngin.hooks.docker.hook_data.DockerHookData[source]
Docker image build hook.
Replicates the functionality of
docker image buildCLI command.kwargs are parsed by
ImageBuildArgs.
- runway.cfngin.hooks.docker.image.push(*, context: runway.context.CfnginContext, **kwargs: Any) runway.cfngin.hooks.docker.hook_data.DockerHookData[source]
Docker image push hook.
Replicates the functionality of
docker image pushCLI command.kwargs are parsed by
ImagePushArgs.
- runway.cfngin.hooks.docker.image.remove(*, context: runway.context.CfnginContext, **kwargs: Any) runway.cfngin.hooks.docker.hook_data.DockerHookData[source]
Docker image push remove.
Replicates the functionality of
docker image pushCLI command.kwargs are parsed by
ImageRemoveArgs.
Hook data models.
These are makeshift data models for use until Runway v2 is released and pydantic can be used.
- class runway.cfngin.hooks.docker.data_models.ElasticContainerRegistry[source]
Bases:
runway.utils.BaseModelAWS Elastic Container Registry.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.cfngin.hooks.docker.data_models.DockerImage[source]
Bases:
runway.utils.BaseModelWrapper for
docker.models.images.Image.- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- classmethod update_forward_refs(**localns: Any) None
Try to update ForwardRefs on fields based on this Model, globalns and localns.
- property uri: runway.utils.MutableMap
Return a mapping of tag to image URI.
- class runway.cfngin.hooks.docker.data_models.ElasticContainerRegistryRepository[source]
Bases:
runway.utils.BaseModelAWS Elastic Container Registry (ECR) Repository.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- classmethod update_forward_refs(**localns: Any) None
Try to update ForwardRefs on fields based on this Model, globalns and localns.
- registry: runway.cfngin.hooks.docker.data_models.ElasticContainerRegistry
Information about an ECR registry.
Docker hook_data object.
- class runway.cfngin.hooks.docker.hook_data.DockerHookData[source]
Bases:
runway.utils.MutableMapDocker hook_data object.
- property client: docker.client.DockerClient
Docker client.
- __delitem__(key: str) None
Implement deletion of self[key].
- Parameters
key – Attribute name to remove from the object.
Example
- __getitem__(key: str) Any
Implement evaluation of self[key].
- Parameters
key – Attribute name to return the value for.
- Returns
The value associated with the provided key/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
Example
- __init__(**kwargs: Any) None
Initialize class.
Provided
kwargsare added to the object as attributes.Example
- __new__(**kwargs)
- __setitem__(key: str, value: Any) None
Implement assignment to self[key].
- Parameters
key – Attribute name to associate with a value.
value – Value of a key/attribute.
Example
- clear() None. Remove all items from D.
- find(query: str, default: Optional[Any] = None, ignore_cache: bool = False) Any
Find a value in the map.
Previously found queries are cached to increase search speed. The cached value should only be used if values are not expected to change.
- Parameters
query – A period delimited string that is split to search for nested values
default – The value to return if the query was unsuccessful.
ignore_cache – Ignore cached value.
- get(key: str, default: Optional[Any] = None) Any
Implement evaluation of self.get.
- Parameters
key – Attribute name to return the value for.
default – Value to return if attribute is not found.
- items() a set-like object providing a view on D's items
- keys() a set-like object providing a view on D's keys
- pop(k[, d]) v, remove specified key and return the corresponding value.
If key is not found, d is returned if given, otherwise KeyError is raised.
- popitem() (k, v), remove and return some (key, value) pair
as a 2-tuple; but raise KeyError if D is empty.
- setdefault(k[, d]) D.get(k,d), also set D[k]=d if k not in D
- update([E, ]**F) None. Update D from mapping/iterable E and F.
If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v
- update_context(context: CfnginContext = None) runway.cfngin.hooks.docker.hook_data.DockerHookData[source]
- update_context(context: None = None) None
Update context object with new the current DockerHookData.
- values() an object providing a view on D's values
- classmethod from_cfngin_context(context: runway.context.CfnginContext) runway.cfngin.hooks.docker.hook_data.DockerHookData[source]
Get existing object or create a new one.
AWS Elastic Container Registry (ECR) hook.
AWS SSM hooks.
AWS SSM Parameter Store hooks.
- class runway.cfngin.hooks.ssm.parameter.ArgsDataModel[source]
Bases:
runway.utils.BaseModelParameter hook args.
- data_type
The data type for a String parameter. Supported data types include plain text and Amazon Machine Image IDs.
- Type
Optional[typing_extensions.Literal[aws:ec2:image, text]]
- force
Skip checking the current value of the parameter, just put it. Can be used alongside
overwriteto always update a parameter.- Type
- key_id
The KMS Key ID that you want to use to encrypt a parameter. Either the default AWS Key Management Service (AWS KMS) key automatically assigned to your AWS account or a custom key. Required for parameters that use the
SecureStringdata type.- Type
Optional[str]
- policies
One or more policies to apply to a parameter. This field takes a JSON array.
- Type
Optional[str]
- tags
Optional metadata that you assign to a resource.
- Type
Optional[List[runway.cfngin.hooks.utils.TagDataModel]]
- tier
The parameter tier to assign to a parameter.
- Type
typing_extensions.Literal[Advanced, Intelligent-Tiering, Standard]
- type
The type of parameter.
- Type
typing_extensions.Literal[String, StringList, SecureString]
- value
The parameter value that you want to add to the system. Standard parameters have a value limit of 4 KB. Advanced parameters have a value limit of 8 KB.
- Type
Optional[str]
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.cfngin.hooks.ssm.parameter.SecureString[source]
Bases:
runway.cfngin.hooks.ssm.parameter._ParameterAWS SSM Parameter Store SecureString Parameter.
- __new__(**kwargs)
- property client: SSMClient
AWS SSM client.
- get() ParameterTypeDef
Get parameter.
- get_current_tags() List[TagTypeDef]
Get Tags currently applied to Parameter.
- post_deploy() runway.cfngin.hooks.ssm.parameter._PutParameterResultTypeDef
Run during the post_deploy stage.
- pre_deploy() runway.cfngin.hooks.ssm.parameter._PutParameterResultTypeDef
Run during the pre_deploy stage.
- put() runway.cfngin.hooks.ssm.parameter._PutParameterResultTypeDef
Put parameter.
Empty init for python import traversal.
Empty init for python import traversal.
Callback URL Retriever.
Dependency pre-hook responsible for ensuring correct callback urls are retrieved or a temporary one is used in it’s place.
- class runway.cfngin.hooks.staticsite.auth_at_edge.callback_url_retriever.HookArgs[source]
Bases:
runway.cfngin.hooks.base.HookArgsBaseModelHook arguments.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- runway.cfngin.hooks.staticsite.auth_at_edge.callback_url_retriever.get(context: runway.context.CfnginContext, *__args: Any, **kwargs: Any) Dict[str, Any][source]
Retrieve the callback URLs for User Pool Client Creation.
When the User Pool is created a Callback URL is required. During a post hook entitled
client_updaterthese Callback URLs are updated to that of the Distribution. Before then we need to ensure that if a Client already exists that the URLs for that client are used to prevent any interruption of service during deploy.Arguments parsed by
HookArgs.- Parameters
context – The context instance.
User Pool Client Updater.
Responsible for updating the User Pool Client with the generated distribution url + callback url paths.
- class runway.cfngin.hooks.staticsite.auth_at_edge.client_updater.HookArgs[source]
Bases:
runway.cfngin.hooks.base.HookArgsBaseModelHook arguments.
- alternate_domains: List[str]
A list of any alternate domains that need to be listed with the primary distribution domain.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- runway.cfngin.hooks.staticsite.auth_at_edge.client_updater.get_redirect_uris(domains: List[str], redirect_path_sign_in: str, redirect_path_sign_out: str) Dict[str, List[str]][source]
Create dict of redirect URIs for AppClient.
- runway.cfngin.hooks.staticsite.auth_at_edge.client_updater.update(context: runway.context.CfnginContext, *__args: Any, **kwargs: Any) bool[source]
Update the callback urls for the User Pool Client.
Required to match the redirect_uri being sent which contains our distribution and alternate domain names.
Arguments parsed by
HookArgs.- Parameters
context – The context instance.
User Pool Client Domain Updater.
- class runway.cfngin.hooks.staticsite.auth_at_edge.domain_updater.HookArgs[source]
Bases:
runway.cfngin.hooks.base.HookArgsBaseModelHook arguments.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- runway.cfngin.hooks.staticsite.auth_at_edge.domain_updater.update(context: runway.context.CfnginContext, *__args: Any, **kwargs: Any) Union[Dict[str, Any], bool][source]
Retrieve/Update the domain name of the specified client.
A domain name is required in order to make authorization and token requests. This prehook ensures we have one available, and if not we create one based on the user pool and client ids.
Arguments parsed by
HookArgs.- Parameters
context – The context instance.
- runway.cfngin.hooks.staticsite.auth_at_edge.domain_updater.delete(context: runway.context.CfnginContext, *__args: Any, **kwargs: Any) Union[Dict[str, Any], bool][source]
Delete the domain if the user pool was created by Runway.
If a User Pool was created by Runway, and populated with a domain, that domain must be deleted prior to the User Pool itself being deleted or an error will occur. This process ensures that our generated domain name is deleted, or skips if not able to find one.
Arguments parsed by
HookArgs.- Parameters
context – The context instance.
CFNgin prehook responsible for creation of Lambda@Edge functions.
- class runway.cfngin.hooks.staticsite.auth_at_edge.lambda_config.HookArgs[source]
Bases:
runway.cfngin.hooks.base.HookArgsBaseModelHook arguments.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- classmethod update_forward_refs(**localns: Any) None
Try to update ForwardRefs on fields based on this Model, globalns and localns.
- redirect_path_refresh: str
The URL path for authorization refresh redirect (Correlates to the refresh auth lambda).
- redirect_path_sign_in: str
The URL path to be redirected to after sign in (Correlates to the parse auth lambda).
- runway.cfngin.hooks.staticsite.auth_at_edge.lambda_config.write(context: CfnginContext, provider: Provider, *__args: Any, **kwargs: Any) Dict[str, Any][source]
Writes/Uploads the configured lambdas for Auth@Edge.
Lambda@Edge does not have the ability to allow Environment variables at the time of this writing. In order to configure our lambdas with dynamic variables we first will go through and update a “shared” template with all of the configuration elements and add that to a temporary folder along with each of the individual Lambda@Edge functions. This temporary folder is then used with the CFNgin awsLambda hook to build the functions.
- runway.cfngin.hooks.staticsite.auth_at_edge.lambda_config.get_nonce_signing_secret(param_name: str, context: runway.context.CfnginContext) str[source]
Retrieve signing secret, generating & storing it first if not present.
Retrieve the ID of the Cognito User Pool.
- class runway.cfngin.hooks.staticsite.auth_at_edge.user_pool_id_retriever.HookArgs[source]
Bases:
runway.cfngin.hooks.base.HookArgsBaseModelHook arguments.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- runway.cfngin.hooks.staticsite.auth_at_edge.user_pool_id_retriever.get(*__args: Any, **kwargs: Any) Dict[str, Any][source]
Retrieve the ID of the Cognito User Pool.
The User Pool can either be supplied via an ARN or by being generated. If the user has supplied an ARN that utilize that, otherwise retrieve the generated id. Used in multiple pre_hooks for Auth@Edge.
Arguments parsed by
HookArgs.
CFNgin hook for building static website.
- class runway.cfngin.hooks.staticsite.build_staticsite.HookArgsOptions[source]
Bases:
runway.cfngin.hooks.base.HookArgsBaseModelHook arguments
optionsblock.- build_steps: List[Union[str, List[str], Dict[str, Union[str, List[str]]]]]
Steps to execute to build the static site.
- pre_build_steps: List[Union[str, List[str], Dict[str, Union[str, List[str]]]]]
Steps to run before building the static site.
- source_hashing: runway.module.staticsite.options.models.RunwayStaticSiteSourceHashingDataModel
Settings for tracking the hash of the source code between runs.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.cfngin.hooks.staticsite.build_staticsite.HookArgs[source]
Bases:
runway.cfngin.hooks.base.HookArgsBaseModelHook arguments.
- options: runway.cfngin.hooks.staticsite.build_staticsite.HookArgsOptions
Hook
optionsblock.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- runway.cfngin.hooks.staticsite.build_staticsite.zip_and_upload(app_dir: str, bucket: str, key: str, session: Optional[boto3.session.Session] = None) None[source]
Zip built static site and upload to S3.
- class runway.cfngin.hooks.staticsite.build_staticsite.OptionsArgTypeDef[source]
Bases:
typing_extensions.TypedDictOptions argument type definition.
- runway.cfngin.hooks.staticsite.build_staticsite.build(context: CfnginContext, provider: Provider, *, options: Optional[OptionsArgTypeDef] = None, **kwargs: Any) Dict[str, Any][source]
Build static site.
Arguments parsed by
HookArgs.
Replicated Lambda Function cleanup warning.
- class runway.cfngin.hooks.staticsite.cleanup.HookArgs[source]
Bases:
runway.cfngin.hooks.base.HookArgsBaseModelHook arguments.
- stack_relative_name: str
Name of the CloudFormation Stack as defined in the config file (no namespace).
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
CFNgin hook for syncing static website to S3 bucket.
- class runway.cfngin.hooks.staticsite.upload_staticsite.HookArgs[source]
Bases:
runway.cfngin.hooks.base.HookArgsBaseModelHook arguments.
- extra_files: List[runway.module.staticsite.options.models.RunwayStaticSiteExtraFileDataModel]
Extra files to sync to the S3 bucket.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- runway.cfngin.hooks.staticsite.upload_staticsite.get_archives_to_prune(archives: List[Dict[str, Any]], hook_data: Dict[str, Any]) List[str][source]
Return list of keys to delete.
- Parameters
archives – The full list of file archives
hook_data – CFNgin hook data
- runway.cfngin.hooks.staticsite.upload_staticsite.sync(context: runway.context.CfnginContext, *__args: Any, **kwargs: Any) bool[source]
Sync static website to S3 bucket.
Arguments parsed by
HookArgs.- Parameters
context – The context instance.
- runway.cfngin.hooks.staticsite.upload_staticsite.update_ssm_hash(context: CfnginContext, session: Session) bool[source]
Update the SSM hash with the new tracking data.
- Parameters
context – Context instance.
session – boto3 session.
- runway.cfngin.hooks.staticsite.upload_staticsite.invalidate_distribution(session: Session, *, domain: str = 'undefined', identifier: str, path: str = '/*', **_: Any) bool[source]
Invalidate the current distribution.
- Parameters
session – The current CFNgin session.
domain – The distribution domain.
identifier – The distribution id.
path – The distribution path.
- runway.cfngin.hooks.staticsite.upload_staticsite.prune_archives(context: CfnginContext, session: Session) bool[source]
Prune the archives from the bucket.
- Parameters
context – The context instance.
session – The CFNgin session.
- runway.cfngin.hooks.staticsite.upload_staticsite.auto_detect_content_type(filename: Optional[str]) Optional[str][source]
Auto detects the content type based on the filename.
- Parameters
filename – A filename to use to auto detect the content type.
- Returns
The content type of the file. None if the content type could not be detected.
- runway.cfngin.hooks.staticsite.upload_staticsite.get_content_type(extra_file: runway.module.staticsite.options.models.RunwayStaticSiteExtraFileDataModel) Optional[str][source]
Return the content type of the file.
- Parameters
extra_file – The extra file configuration.
- Returns
The content type of the extra file. If ‘content_type’ is provided then that is returned, otherwise it is auto detected based on the name.
- runway.cfngin.hooks.staticsite.upload_staticsite.get_content(extra_file: runway.module.staticsite.options.models.RunwayStaticSiteExtraFileDataModel) Optional[str][source]
Get serialized content based on content_type.
- Parameters
extra_file – The extra file configuration.
- Returns
Serialized content based on the content_type.
- runway.cfngin.hooks.staticsite.upload_staticsite.calculate_hash_of_extra_files(extra_files: List[runway.module.staticsite.options.models.RunwayStaticSiteExtraFileDataModel]) str[source]
Return a hash of all of the given extra files.
All attributes of the extra file object are included when hashing: name, content_type, content, and file data.
- Parameters
extra_files – The list of extra file configurations.
- Returns
The hash of all the files.
- runway.cfngin.hooks.staticsite.upload_staticsite.get_ssm_value(session: Session, name: str) Optional[str][source]
Get the ssm parameter value.
- Parameters
session – The boto3 session.
name – The parameter name.
- Returns
The parameter value.
- runway.cfngin.hooks.staticsite.upload_staticsite.set_ssm_value(session: Session, name: str, value: Any, description: str = '') None[source]
Set the ssm parameter.
- Parameters
session – The boto3 session.
name – The name of the parameter.
value – The value of the parameter.
description – A description of the parameter.
- runway.cfngin.hooks.staticsite.upload_staticsite.sync_extra_files(context: runway.context.CfnginContext, bucket: str, extra_files: List[runway.module.staticsite.options.models.RunwayStaticSiteExtraFileDataModel], **kwargs: Any) List[str][source]
Sync static website extra files to S3 bucket.
- Parameters
context – The context instance.
bucket – The static site bucket name.
extra_files – List of files and file content that should be uploaded.
Utility functions for website build/upload.
- runway.cfngin.hooks.staticsite.utils.calculate_hash_of_files(files: Iterable[StrPath], root: Path) str[source]
Return a hash of all of the given files at the given root.
- Parameters
files – file names to include in the hash calculation, relative to
root.root – base directory to analyze files in.
- Returns
A hash of the hashes of the given files.
- runway.cfngin.hooks.staticsite.utils.get_hash_of_files(root_path: pathlib.Path, directories: Optional[List[Dict[str, Union[str, List[str]]]]] = None) str[source]
Generate md5 hash of files.
- Parameters
root_path – Base directory where all paths will be relative to. This should already be resolve to an absolute path.
directories – List of mappings that describe the paths to hash and files to exclude.
- runway.cfngin.hooks.staticsite.utils.get_ignorer(path: pathlib.Path, additional_exclusions: Optional[List[str]] = None) igittigitt.igittigitt.IgnoreParser[source]
Create gitignore filter from directory
.gitignorefile.- Parameters
path – Top-level directory that the gitignore filter will be created for. This directory and it’s subdirectories will be searched for
.gitignorefiles to use.additional_exclusions – Additional gitignore patterns to add.
CFNgin hooks for AWS Certificate Manager.
- class runway.cfngin.hooks.acm.HookArgs[source]
Bases:
runway.cfngin.hooks.base.HookArgsBaseModelHook arguments.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.cfngin.hooks.acm.Certificate[source]
Bases:
runway.cfngin.hooks.base.HookHook for managing a AWS::CertificateManager::Certificate.
- Keyword Arguments
alt_names (Optional[List[str]]) – Additional FQDNs to be included in the Subject Alternative Name extension of the ACM certificate. For example, you can add www.example.net to a certificate for which the domain field is www.example.com if users can reach your site by using either name.
domain (str) – The fully qualified domain name (FQDN), such as www.example.com, with which you want to secure an ACM certificate. Use an asterisk (
*) to create a wildcard certificate that protects several sites in the same domain. For example, *.example.com protects www.example.com, site.example.com, and images.example.com.hosted_zone_id (str) – The ID of the Route 53 Hosted Zone that contains the resource record sets that you want to change. This must exist in the same account that the certificate will be created in.
stack_name (Optional[str]) – Provide a name for the stack used to create the certificate. If not provided, the domain is used (replacing
.with-).ttl (Optional[int]) – The resource record cache time to live (TTL), in seconds. (default:
300)
Example
pre_deploy: example-wildcard-cert: path: runway.cfngin.hooks.acm.Certificate required: true args: domain: '*.example.com' hosted_zone_id: ${xref example-com::HostedZoneId}
- ARGS_PARSER
alias of
runway.cfngin.hooks.acm.HookArgs
- __init__(context: CfnginContext, provider: Provider, **kwargs: Any) None[source]
Instantiate class.
- Parameters
context – Context instance. (passed in by CFNgin)
provider – Provider instance. (passed in by CFNgin)
- get_certificate(interval: int = 5) str[source]
Get the certificate being created by a CloudFormation.
- Parameters
interval – Number of seconds to wait between attempts.
- Returns
Certificate ARN.
- get_validation_record(cert_arn: Optional[str] = None, *, interval: int = 5, status: str = 'PENDING_VALIDATION') ResourceRecordTypeDef[source]
Get validation record from the certificate being created.
- Parameters
cert_arn – ARN of the certificate to validate.
interval – Number of seconds to wait between attempts.
status – Validation status to look for when finding a validation record. Typically only “PENDING_VALIDATION” or “SUCCESS” will be used.
- Raises
ValueError – No pending or too many pending certificates.
- put_record_set(record_set: ResourceRecordTypeDef) None[source]
Create/update a record set on a Route 53 Hosted Zone.
- Parameters
record_set – Record set to be added to Route 53.
- remove_validation_records(records: Optional[List[ResourceRecordTypeDef]] = None) None[source]
Remove all record set entries used to validate an ACM Certificate.
- Parameters
records – List of validation records to remove from Route 53. This can be provided in cases were the certificate has been deleted during a rollback.
- update_record_set(record_set: ResourceRecordTypeDef) None[source]
Update a validation record set when the cert has not changed.
- Parameters
record_set – Record set to be updated in Route 53.
- __new__(**kwargs)
- deploy_stack(stack: Optional[Stack] = None, wait: bool = False) Status
Deploy a stack.
- Parameters
stack – A stack to act on.
wait – Wither to wait for the stack to complete before returning.
- Returns
Ending status of the stack.
- destroy(records: Optional[List[ResourceRecordTypeDef]] = None, skip_r53: bool = False) bool[source]
Destroy an ACM certificate.
- Parameters
records – List of validation records to remove from Route 53. This can be provided in cases were the certificate has been deleted during a rollback.
skip_r53 – Skip the removal of validation records.
- destroy_stack(stack: Optional[Stack] = None, wait: bool = False) Status
Destroy a stack.
- Parameters
stack – A stack to act on.
wait – Wither to wait for the stack to complete before returning.
- Returns
Ending status of the stack.
- generate_stack(**kwargs: Any) runway.cfngin.stack.Stack
Create a CFNgin Stack object.
- get_template_description(suffix: Optional[str] = None) str
Generate a template description.
- Parameters
suffix – Suffix to append to the end of a CloudFormation template description.
- property tags: troposphere.Tags
Return tags that should be applied to any resource being created.
AWS Lambda hook.
- runway.cfngin.hooks.aws_lambda.copydir(source: str, destination: str, includes: List[str], excludes: Optional[List[str]] = None, follow_symlinks: bool = False) None[source]
Extend the functionality of shutil.
Correctly copies files and directories in a source directory.
- Parameters
source – Source directory.
destination – Destination directory.
includes – Glob patterns for files to include.
excludes – Glob patterns for files to exclude.
follow_symlinks – If true, symlinks will be included in the resulting zip file.
- runway.cfngin.hooks.aws_lambda.find_requirements(root: str) Optional[Dict[str, bool]][source]
Identify Python requirement files.
- Parameters
root – Path that should be searched for files.
- Returns
Name of supported requirements file and whether it was found. If none are found,
Noneis returned.
- runway.cfngin.hooks.aws_lambda.should_use_docker(dockerize_pip: Optional[typing.Union[bool, typing_extensions.Literal[false, False, no, No, non - linux, true, True, yes, Yes]]] = None) bool[source]
Assess if Docker should be used based on the value of args.
- Parameters
dockerize_pip – Value to assess if Docker should be used for pip.
- runway.cfngin.hooks.aws_lambda.handle_requirements(package_root: str, dest_path: str, requirements: Dict[str, bool], pipenv_timeout: int = 300, python_path: Optional[str] = None, use_pipenv: bool = False) str[source]
Use the correct requirements file.
- Parameters
package_root – Base directory containing a requirements file.
dest_path – Where to output the requirements file if one needs to be created.
requirements – Map of requirement file names and whether they exist.
pipenv_timeout – Seconds to wait for a subprocess to complete.
python_path – Explicit python interpreter to be used. Requirement file generators must be installed and executable using
-mif provided.use_pipenv – Explicitly use pipenv to export a Pipfile as requirements.txt.
- Returns
Path to the final requirements.txt
- Raises
NotImplementedError – When a requirements file is not found. This should never be encountered but is included just in case.
- runway.cfngin.hooks.aws_lambda.dockerized_pip(work_dir: str, client: Optional[docker.client.DockerClient] = None, runtime: Optional[str] = None, docker_file: Optional[str] = None, docker_image: Optional[str] = None, python_dontwritebytecode: bool = False, **_: Any) None[source]
Run pip with docker.
- Parameters
work_dir – Work directory for docker.
client – Custom docker client.
runtime – Lambda runtime. Must provide one of
runtime,docker_file, ordocker_image.docker_file – Path to a Dockerfile to build an image. Must provide one of
runtime,docker_file, ordocker_image.docker_image – Local or remote docker image to use. Must provide one of
runtime,docker_file, ordocker_image.python_dontwritebytecode – Don’t write bytecode.
- runway.cfngin.hooks.aws_lambda.select_bucket_region(custom_bucket: Optional[str], hook_region: Optional[str], cfngin_bucket_region: Optional[str], provider_region: str) str[source]
Return the appropriate region to use when uploading functions.
Select the appropriate region for the bucket where lambdas are uploaded in.
- Parameters
custom_bucket – The custom bucket name provided by the bucket kwarg of the aws_lambda hook, if provided.
hook_region – The contents of the bucket_region argument to the hook.
cfngin_bucket_region – The contents of the
cfngin_bucket_regionglobal setting.provider_region – The region being used by the provider.
- Returns
The appropriate region string.
- runway.cfngin.hooks.aws_lambda.upload_lambda_functions(context: CfnginContext, provider: Provider, **kwargs: Any)[source]
Build Lambda payloads from user configuration and upload them to S3.
Constructs ZIP archives containing files matching specified patterns for each function, uploads the result to Amazon S3, then stores objects (of type
troposphere.awslambda.Code) in the context’s hook data, ready to be referenced in blueprints.Configuration consists of some global options, and a dictionary of function specifications. In the specifications, each key indicating the name of the function (used for generating names for artifacts), and the value determines what files to include in the ZIP (see more details below).
Payloads are uploaded to either a custom bucket or the CFNgin default bucket, with the key containing it’s checksum, to allow repeated uploads to be skipped in subsequent runs.
The configuration settings are documented as keyword arguments below.
- Parameters
provider – Provider instance. (passed in by CFNgin)
context – Context instance. (passed in by CFNgin)
- Keyword Arguments
bucket (Optional[str]) – Custom bucket to upload functions to. Omitting it will cause the default CFNgin bucket to be used.
bucket_region (Optional[str]) – The region in which the bucket should exist. If not given, the region will be either be that of the global
cfngin_bucket_regionsetting, or else the region in use by the provider.prefix (Optional[str]) – S3 key prefix to prepend to the uploaded zip name.
follow_symlinks (Optional[bool]) – Will determine if symlinks should be followed and included with the zip artifact. (default:
False)payload_acl (Optional[str]) – The canned S3 object ACL to be applied to the uploaded payload. (default: private)
functions (Dict[str, Any]) –
Configurations of desired payloads to build. Keys correspond to function names, used to derive key names for the payload. Each value should itself be a dictionary, with the following data:
- docker_file (Optional[str])
Path to a local DockerFile that will be built and used for
dockerize_pip. Must provide exactly one ofdocker_file,docker_image, orruntime.- docker_image (Optional[str])
Custom Docker image to use with
dockerize_pip. Must provide exactly one ofdocker_file,docker_image, orruntime.- dockerize_pip (Optional[Union[str, bool]])
Whether to use Docker when preparing package dependencies with pip. Can be set to True/False or the special string ‘non-linux’ which will only run on non Linux systems. To use this option Docker must be installed.
- exclude (Optional[Union[str, List[str]]])
Pattern or list of patterns of files to exclude from the payload. If provided, any files that match will be ignored, regardless of whether they match an inclusion pattern.
Commonly ignored files are already excluded by default, such as
.git,.svn,__pycache__,*.pyc,.gitignore, etc.- include (Optional[Union[str, List[str]]])
Pattern or list of patterns of files to include in the payload. If provided, only files that match these patterns will be included in the payload.
Omitting it is equivalent to accepting all files that are not otherwise excluded.
- path (str)
Base directory of the Lambda function payload content. If it not an absolute path, it will be considered relative to the directory containing the CFNgin configuration file in use.
Files in this directory will be added to the payload ZIP, according to the include and exclude patterns. If no patterns are provided, all files in this directory (respecting default exclusions) will be used.
Files are stored in the archive with path names relative to this directory. So, for example, all the files contained directly under this directory will be added to the root of the ZIP file.
- pipenv_lock_timeout (Optional[int])
Time in seconds to wait while creating lock file with pipenv.
- pipenv_timeout (Optional[int])
Time in seconds to wait while running pipenv.
- python_path (Optional[str])
Absolute path to a python interpreter to use for
pip/pipenvactions. If not provided, the current python interpreter will be used forpipandpipenvwill be used from the current$PATH.- runtime (Optional[str])
Runtime of the AWS Lambda Function being uploaded. Used with
dockerize_pipto automatically select the appropriate Docker image to use. Must provide exactly one ofdocker_file,docker_image, orruntime.- use_pipenv (Optional[bool])
Explicitly use Pipfile/Pipfile.lock to prepare package dependencies even if a requirements.txt file is found.
Examples
pre_deploy: - path: runway.cfngin.hooks.aws_lambda.upload_lambda_functions required: true enabled: true data_key: lambda args: bucket: custom-bucket follow_symlinks: true prefix: cloudformation-custom-resources/ payload_acl: authenticated-read functions: MyFunction: path: ./lambda_functions dockerize_pip: non-linux use_pipenv: true runtime: python3.9 include: - '*.py' - '*.txt' exclude: - '*.pyc' - test/
from troposphere.awslambda import Function from runway.cfngin.blueprints.base import Blueprint class LambdaBlueprint(Blueprint): def create_template(self): code = self.context.hook_data['lambda']['MyFunction'] self.template.add_resource( Function( 'MyFunction', Code=code, Handler='my_function.handler', Role='...', Runtime='python2.7' ) )
Base class for CFNgin hooks.
- class runway.cfngin.hooks.base.HookArgsBaseModel[source]
Bases:
runway.utils.BaseModelBase model for hook args.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.cfngin.hooks.base.Hook[source]
Bases:
runway.cfngin.hooks.protocols.CfnginHookProtocolBase class for hooks.
Not all hooks need to be classes and not all classes need to be hooks.
- args
Keyword arguments passed to the hook, loaded into a MutableMap object.
- Type
- blueprint
Blueprint generated by the hook if it will be deploying a stack.
- Type
Optional[Blueprint]
- context
Context instance. (passed in by CFNgin)
- Type
- provider Provider instance.
- Type
passed in by CFNgin
- ARGS_PARSER
Class used to parse arguments passed to the hook.
- __init__(context: CfnginContext, provider: Provider, **kwargs: Any) None[source]
Instantiate class.
- Parameters
context – Context instance. (passed in by CFNgin)
provider – Provider instance. (passed in by CFNgin)
- property tags: troposphere.Tags
Return tags that should be applied to any resource being created.
- generate_stack(**kwargs: Any) runway.cfngin.stack.Stack[source]
Create a CFNgin Stack object.
- get_template_description(suffix: Optional[str] = None) str[source]
Generate a template description.
- Parameters
suffix – Suffix to append to the end of a CloudFormation template description.
- deploy_stack(stack: Optional[Stack] = None, wait: bool = False) Status[source]
Deploy a stack.
- Parameters
stack – A stack to act on.
wait – Wither to wait for the stack to complete before returning.
- Returns
Ending status of the stack.
- destroy_stack(stack: Optional[Stack] = None, wait: bool = False) Status[source]
Destroy a stack.
- Parameters
stack – A stack to act on.
wait – Wither to wait for the stack to complete before returning.
- Returns
Ending status of the stack.
- __new__(**kwargs)
- class runway.cfngin.hooks.base.HookDeployAction[source]
Bases:
runway.cfngin.actions.deploy.ActionDeploy action that can be used from hooks.
- __init__(context: CfnginContext, provider: Provider)[source]
Instantiate class.
- Parameters
context – The context for the current run.
provider – The provider instance.
- __new__(**kwargs)
- static build_parameters(stack: Stack, provider_stack: Optional[StackTypeDef] = None) List[ParameterTypeDef]
Build the CloudFormation Parameters for our stack.
- Parameters
stack – A CFNgin stack.
provider_stack – An optional CFNgin provider object.
- Returns
The parameters for the given stack
- post_run(*, dump: Union[bool, str] = False, outline: bool = False, **_: Any) None
Any steps that need to be taken after running the action.
- pre_run(*, dump: Union[bool, str] = False, outline: bool = False, **_: Any) None
Any steps that need to be taken prior to running the action.
- class runway.cfngin.hooks.base.HookDestroyAction[source]
Bases:
runway.cfngin.hooks.base.HookDeployActionDestroy action that can be used from hooks.
- __init__(context: CfnginContext, provider: Provider)
Instantiate class.
- Parameters
context – The context for the current run.
provider – The provider instance.
- __new__(**kwargs)
- static build_parameters(stack: Stack, provider_stack: Optional[StackTypeDef] = None) List[ParameterTypeDef]
Build the CloudFormation Parameters for our stack.
- Parameters
stack – A CFNgin stack.
provider_stack – An optional CFNgin provider object.
- Returns
The parameters for the given stack
- post_run(*, dump: Union[bool, str] = False, outline: bool = False, **_: Any) None
Any steps that need to be taken after running the action.
- pre_run(*, dump: Union[bool, str] = False, outline: bool = False, **_: Any) None
Any steps that need to be taken prior to running the action.
CFNgin hook for cleaning up resources prior to CFN stack deletion.
- class runway.cfngin.hooks.cleanup_s3.PurgeBucketHookArgs[source]
Bases:
runway.utils.BaseModelHook arguments for
purge_bucket.- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
CFNgin hook for cleaning up resources prior to CFN stack deletion.
- class runway.cfngin.hooks.cleanup_ssm.DeleteParamHookArgs[source]
Bases:
runway.utils.BaseModelHook arguments for
delete_param.- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
Command hook.
- class runway.cfngin.hooks.command.RunCommandHookArgs[source]
Bases:
runway.utils.BaseModelHook arguments for
run_command.- capture: bool
If enabled, capture the command’s stdout and stderr, and return them in the hook result.
- env: Optional[Dict[str, str]]
Dictionary of environment variable overrides for the command context. Will be merged with the current environment.
- interactive: bool
If enabled, allow the command to interact with stdin. Otherwise, stdin will be set to the null device.
- quiet: bool
Redirect the command’s stdout and stderr to the null device, silencing all output. Should not be enabled if
captureis also enabled.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.cfngin.hooks.command.RunCommandResponseTypeDef[source]
Bases:
typing_extensions.TypedDictResponse from run_command.
- runway.cfngin.hooks.command.run_command(*__args: Any, **kwargs: Any) runway.cfngin.hooks.command.RunCommandResponseTypeDef[source]
Run a custom command as a hook.
Arguments not parsed by the data model will be forwarded to the
subprocess.Popenfunction. Interesting ones include:cwdandshell.Examples
pre_deploy: command_copy_environment: path: runway.cfngin.hooks.command.run_command required: true enabled: true data_key: copy_env args: command: ['cp', 'environment.template', 'environment'] command_git_rev_parse: path: runway.cfngin.hooks.command.run_command required: true enabled: true data_key: get_git_commit args: command: ['git', 'rev-parse', 'HEAD'] cwd: ./my-git-repo capture: true command_npm_install: path: runway.cfngin.hooks.command.run_command args: command: '`cd $PROJECT_DIR/project; npm install`' env: PROJECT_DIR: ./my-project shell: true
AWS ECS hook.
- class runway.cfngin.hooks.ecs.CreateClustersHookArgs[source]
Bases:
runway.utils.BaseModelHook arguments for
create_clusters.- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.cfngin.hooks.ecs.CreateClustersResponseTypeDef[source]
Bases:
typing_extensions.TypedDictResponse from create_clusters.
- runway.cfngin.hooks.ecs.create_clusters(context: runway.context.CfnginContext, *__args: Any, **kwargs: Any) runway.cfngin.hooks.ecs.CreateClustersResponseTypeDef[source]
Create ECS clusters.
- Parameters
context – CFNgin context object.
AWS IAM hook.
- class runway.cfngin.hooks.iam.CreateEcsServiceRoleHookArgs[source]
Bases:
runway.utils.BaseModelHook arguments for
create_ecs_service_role.- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.cfngin.hooks.iam.EnsureServerCertExistsHookArgs[source]
Bases:
runway.utils.BaseModelHook arguments for
ensure_server_cert_exists.- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- runway.cfngin.hooks.iam.create_ecs_service_role(context: runway.context.CfnginContext, *__args: Any, **kwargs: Any) bool[source]
Create ecsServiceRole IAM role.
https://docs.aws.amazon.com/AmazonECS/latest/developerguide/using-service-linked-roles.html
- Parameters
context – Context instance. (passed in by CFNgin)
AWS EC2 keypair hook.
- class runway.cfngin.hooks.keypair.EnsureKeypairExistsHookArgs[source]
Bases:
runway.utils.BaseModelHook arguments for
ensure_keypair_exists.- public_key_path: Optional[str]
Path to a public key file to be imported instead of generating a new key. Incompatible with the SSM options, as the private key will not be available for storing.
- ssm_key_id: Optional[str]
ID of a KMS key to encrypt the SSM parameter with. If omitted, the default key will be used.
- ssm_parameter_name: Optional[str]
Path to an SSM store parameter to receive the generated private key instead of importing it or storing it locally.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.cfngin.hooks.keypair.KeyPairInfo[source]
Bases:
typing_extensions.TypedDictValue returned from get_existing_key_pair.
- runway.cfngin.hooks.keypair.get_existing_key_pair(ec2: EC2Client, keypair_name: str) Optional[KeyPairInfo][source]
Get existing keypair.
- runway.cfngin.hooks.keypair.import_key_pair(ec2: EC2Client, keypair_name: str, public_key_data: bytes) ImportKeyPairResultTypeDef[source]
Import keypair.
- runway.cfngin.hooks.keypair.read_public_key_file(path: pathlib.Path) Optional[bytes][source]
Read public key file.
- runway.cfngin.hooks.keypair.create_key_pair_from_public_key_file(ec2: EC2Client, keypair_name: str, public_key_path: Path) Optional[KeyPairInfo][source]
Create keypair from public key file.
- runway.cfngin.hooks.keypair.create_key_pair_in_ssm(ec2: EC2Client, ssm: SSMClient, keypair_name: str, parameter_name: str, kms_key_id: Optional[str] = None) Optional[KeyPairInfo][source]
Create keypair in SSM.
- runway.cfngin.hooks.keypair.create_key_pair(ec2: EC2Client, keypair_name: str) KeyPairTypeDef[source]
Create keypair.
- runway.cfngin.hooks.keypair.create_key_pair_local(ec2: EC2Client, keypair_name: str, dest_dir: Path) Optional[KeyPairInfo][source]
Create local keypair.
- runway.cfngin.hooks.keypair.interactive_prompt(keypair_name: str) Tuple[typing.Optional[typing_extensions.Literal[create, import]], typing.Optional[str]][source]
Interactive prompt.
- runway.cfngin.hooks.keypair.ensure_keypair_exists(context: runway.context.CfnginContext, *__args: Any, **kwargs: Any) runway.cfngin.hooks.keypair.KeyPairInfo[source]
Ensure a specific keypair exists within AWS.
If the key doesn’t exist, upload it.
Protocols for structural typing.
For more information on protocols, refer to PEP 544.
- class runway.cfngin.hooks.protocols.CfnginHookArgsProtocol[source]
Bases:
typing_extensions.ProtocolProtocol for CFNgin hook arguments class.
This class defines a structural interface for all CFNgin hook argument classes. It is recommended to use the provided base class in place of this when authoring a new argument class.
- abstract get(__name: str) Optional[Any][source]
- abstract get(__name: str, __default: Union[Any, runway.cfngin.hooks.protocols._T]) Union[Any, runway.cfngin.hooks.protocols._T]
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- __init__(*args, **kwargs)
- __new__(**kwargs)
- class runway.cfngin.hooks.protocols.CfnginHookProtocol[source]
Bases:
typing_extensions.ProtocolProtocol for CFNgin hooks.
This class defines a structural interface for all CFNgin hook classes. Classes used for hooks do not need to subclass this hook. They only need to implement a similar interface. While not required, it is still acceptable to subclass this class for full type checking of a hook class.
- args: runway.cfngin.hooks.protocols.CfnginHookArgsProtocol
Arguments passed to the hook and parsed into an object.
- abstract __init__(context: runway.context.CfnginContext, **_kwargs: Any) None[source]
Structural __init__ method.
This should not be called. Pylint will erroneously warn about “super-init-not-called” if using this class as a subclass. This should be disabled in-line until the bug reports for this issue is resolved.
- abstract post_deploy() Any[source]
Run during the post_deploy stage.
- Returns
A “truthy” value if the hook was successful or a “falsy” value if the hook failed.
- __new__(**kwargs)
- abstract post_destroy() Any[source]
Run during the post_destroy stage.
- Returns
A “truthy” value if the hook was successful or a “falsy” value if the hook failed.
AWS Route 53 hook.
- class runway.cfngin.hooks.route53.CreateDomainHookArgs[source]
Bases:
runway.utils.BaseModelHook arguments for
create_domain.- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
Hook utils.
- class runway.cfngin.hooks.utils.BlankBlueprint[source]
Bases:
runway.cfngin.blueprints.base.BlueprintBlueprint that can be built programmatically.
- __init__(name: str, context: runway.context.CfnginContext, *, description: Optional[str] = None, mappings: Optional[Dict[str, Dict[str, Any]]] = None, template: Optional[troposphere.Template] = None, **_: Any)
Instantiate class.
- Parameters
name – A name for the blueprint.
context – Context the blueprint is being executed under.
description – The description of the CloudFormation template that will be generated by this blueprint.
mappings – CloudFormation Mappings to be used in the template during the rendering process.
template – Optionally, provide a preexisting Template.
Changed in version 2.0.0: Added
template.Changed in version 2.0.0: Class only takes 2 positional arguments. The rest are now keyword arguments.
- __new__(**kwargs)
- add_output(name: str, value: Any) None
Add an output to the template.
Wrapper for
self.template.add_output(Output(name, Value=value)).- Parameters
name – The name of the output to create.
value – The value to put in the output.
- property cfn_parameters: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters.
- property defined_variables: Dict[str, BlueprintVariableTypeDef]
Return a copy of
VARIABLESto avoid accidental modification of the ClassVar.Changed in version 2.0.0: Changed from a method to a property.
- get_cfn_parameters() Dict[str, Union[List[Any], str]]
Return a dictionary of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
cfn_parameters.- Returns
Variables that need to be submitted as CloudFormation Parameters.
- get_output_definitions() Dict[str, Dict[str, Any]]
Get the output definitions.
Deprecated since version 2.0.0: Replaced by
output_definitions.- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- get_parameter_definitions() Dict[str, BlueprintVariableTypeDef]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.Deprecated since version 2.0.0: Replaced by
parameter_definitions.- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- get_parameter_values() Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.Deprecated since version 2.0.0: Replaced by
parameter_values.- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- get_required_parameter_definitions() Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
Deprecated since version 2.0.0: Replaced by
required_parameter_definitions.- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- get_variables() Dict[str, Any]
Return a dictionary of variables available to the template.
These variables will have been defined within VARIABLES or self.defined_variables. Any variable value that contains a lookup will have been resolved.
Deprecated since version 2.0.0: Replaced by
variables.- Returns
Variables available to the template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
- property output_definitions: Dict[str, Dict[str, Any]]
Get the output definitions.
New in version 2.0.0.
- Returns
Output definitions. Keys are output names, the values are dicts containing key/values for various output properties.
- property parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Get the parameter definitions to submit to CloudFormation.
Any variable definition whose type is an instance of
CFNTypewill be returned as a CloudFormation Parameter.New in version 2.0.0.
- Returns
Parameter definitions. Keys are parameter names, the values are dicts containing key/values for various parameter properties.
- property parameter_values: Dict[str, Union[List[Any], str]]
Return a dict of variables with type
CFNType.New in version 2.0.0.
- Returns
Variables that need to be submitted as CloudFormation Parameters. Will be a dictionary of <parameter name>: <parameter value>.
- read_user_data(user_data_path: str) str
Read and parse a user_data file.
- Parameters
user_data_path – Path to the userdata file.
- property required_parameter_definitions: Dict[str, BlueprintVariableTypeDef]
Return all template parameters that do not have a default value.
New in version 2.0.0.
- Returns
Dict of required CloudFormation Parameters for the blueprint. Will be a dictionary of
<parameter name>: <parameter attributes>.
- resolve_variables(provided_variables: List[runway.variables.Variable]) None
Resolve the values of the blueprint variables.
This will resolve the values of the VARIABLES with values from the env file, the config, and any lookups resolved.
- Parameters
provided_variables – List of provided variables.
- set_template_description(description: str) None
Add a description to the Template.
- Parameters
description – A description to be added to the resulting template.
- to_json(variables: Optional[Dict[str, Any]] = None) str
Render the blueprint and return the template in json form.
- Parameters
variables – Dictionary providing/overriding variable values.
- property variables: Dict[str, Any]
Return a Dict of variables available to the Template.
These variables will have been defined within
VARIABLESordefined_variables. Any variable value that contains a Lookup will have been resolved.New in version 2.0.0.
- Returns
Variables available to the Template.
- Raises
UnresolvedBlueprintVariables – If variables are unresolved.
- class runway.cfngin.hooks.utils.TagDataModel[source]
Bases:
runway.utils.BaseModelAWS Resource Tag data model.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- runway.cfngin.hooks.utils.handle_hooks(stage: str, hooks: List[CfnginHookDefinitionModel], provider: Provider, context: CfnginContext)[source]
Handle pre/post_deploy hooks.
These are pieces of code that we want to run before/after deploying stacks.
- Parameters
stage – The current stage (pre_run, post_run, etc).
hooks – Hooks to execute.
provider – Provider instance.
context – Context instance.
CFNgin logger.
- class runway.cfngin.logger.ColorFormatter[source]
Bases:
logging.FormatterHandles colorizing formatted log messages if color provided.
- format(record: logging.LogRecord) str[source]
Format log message.
- __init__(fmt=None, datefmt=None, style='%', validate=True)
Initialize the formatter with specified format strings.
Initialize the formatter either with the specified format string, or a default as described above. Allow for specialized date formatting with the optional datefmt argument. If datefmt is omitted, you get an ISO8601-like (or RFC 3339-like) format.
Use a style parameter of ‘%’, ‘{’ or ‘$’ to specify that you want to use one of %-formatting,
str.format()({}) formatting orstring.Templateformatting in your format string.Changed in version 3.2: Added the
styleparameter.
- __new__(**kwargs)
- converter()
- localtime([seconds]) -> (tm_year,tm_mon,tm_mday,tm_hour,tm_min,
tm_sec,tm_wday,tm_yday,tm_isdst)
Convert seconds since the Epoch to a time tuple expressing local time. When ‘seconds’ is not passed in, convert the current time instead.
- formatException(ei)
Format and return the specified exception information as a string.
This default implementation just uses traceback.print_exception()
- formatStack(stack_info)
This method is provided as an extension point for specialized formatting of stack information.
The input data is a string as returned from a call to
traceback.print_stack(), but with the last trailing newline removed.The base implementation just returns the value passed in.
- formatTime(record, datefmt=None)
Return the creation time of the specified LogRecord as formatted text.
This method should be called from format() by a formatter which wants to make use of a formatted time. This method can be overridden in formatters to provide for any specific requirement, but the basic behaviour is as follows: if datefmt (a string) is specified, it is used with time.strftime() to format the creation time of the record. Otherwise, an ISO8601-like (or RFC 3339-like) format is used. The resulting string is returned. This function uses a user-configurable function to convert the creation time to a tuple. By default, time.localtime() is used; to change this for a particular formatter instance, set the ‘converter’ attribute to a function with the same signature as time.localtime() or time.gmtime(). To change it for all formatters, for example if you want all logging times to be shown in GMT, set the ‘converter’ attribute in the Formatter class.
- usesTime()
Check if the format uses the creation time of the record.
CFNgin lookups.
- runway.cfngin.lookups.register_lookup_handler(lookup_type: str, handler_or_path: Union[str, Type[runway.lookups.handlers.base.LookupHandler]]) None[source]
Register a lookup handler.
- Parameters
lookup_type – Name to register the handler under.
handler_or_path – A function or a path to a handler.
- runway.cfngin.lookups.unregister_lookup_handler(lookup_type: str) None[source]
Unregister the specified lookup type.
This is useful when testing various lookup types if you want to unregister the lookup type after the test runs.
- Parameters
lookup_type – Name of the lookup type to unregister.
Import modules.
AMI lookup.
- class runway.cfngin.lookups.handlers.ami.ArgsDataModel[source]
Bases:
runway.utils.BaseModelArguments data model.
Any other arguments specified are sent as filters to the AWS API. For example,
architecture:x86_64will add a filter.- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- exception runway.cfngin.lookups.handlers.ami.ImageNotFound[source]
Bases:
ExceptionImage not found.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- class runway.cfngin.lookups.handlers.ami.AmiLookup[source]
Bases:
runway.lookups.handlers.base.LookupHandlerAMI lookup.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
- TYPE_NAME: Final[typing_extensions.Literal[ami]] = 'ami'
Name that the Lookup is registered as.
- classmethod parse(value: str) Tuple[str, Dict[str, str]][source]
Parse the value passed to the lookup.
This overrides the default parsing to account for special requirements.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod handle(value: str, context: runway.context.CfnginContext, *_AmiLookup__args: Any, **_AmiLookup__kwargs: Any) str[source]
Fetch the most recent AMI Id using a filter.
- Parameters
value – Parameter(s) given to this lookup.
context – Context instance.
Example
The above fetches the most recent AMI where owner is self account or amazon and the ami name matches the regex described, the architecture will be either x64 or i386
You can also optionally specify the region in which to perform the AMI lookup.
Dedicated lookup for use with AwsLambdaHook based hooks.
To use this hook, there must be a
AwsLambdaHook based hook defined
in the pre_deploy section of the CFNgin configuration file.
This hook must also define a data_key that is unique within
the CFNgin configuration file (it can be reused in other CFNgin configuration files).
The data_key is then passed to the lookup as it’s input/query.
This allows the lookup to function during a runway plan.
- class runway.cfngin.lookups.handlers.awslambda.AwsLambdaLookup[source]
Bases:
runway.lookups.handlers.base.LookupHandlerLookup for AwsLambdaHook responses.
- classmethod get_deployment_package_data(context: CfnginContext, data_key: str) AwsLambdaHookDeployResponse[source]
Get the response of an AwsLambdaHook run.
- Parameters
context – CFNgin context object.
data_key – The value of the
data_keyfield as assigned in a Hook definition.
- Returns
The
AwsLambdaHookresponse parsed into a data model. This will come from hook data if it exists or it will be calculated and added to hook data for future use.- Raises
TypeError – The data stored in hook data does not align with the expected data model.
- static get_required_hook_definition(config: CfnginConfig, data_key: str) CfnginHookDefinitionModel[source]
Get the required Hook definition from the CFNgin config.
Currently, this only supports finding the data_key pre_deploy.
- Parameters
config – CFNgin config being processed.
data_key – The value of the
data_keyfield as assigned in a Hook definition.
- Returns
The Hook definition set to use the provided
data_key.- Raises
ValueError – Either a Hook definition was not found for the provided
data_keyor, more than one was found.
- classmethod handle(value: str, context: Union[CfnginContext, RunwayContext], *_args: Any, **_kwargs: Any) AwsLambdaHookDeployResponse[source]
Retrieve metadata for an AWS Lambda deployment package.
- Parameters
value – Value to resolve.
context – The current context object.
- Returns
The full
AwsLambdaHookDeployResponsedata model.
- static init_hook_class(context: CfnginContext, hook_def: CfnginHookDefinitionModel) AwsLambdaHook[Any][source]
Initialize AwsLambdaHook subclass instance.
- Parameters
context – CFNgin context object.
hook_def – The
AwsLambdaHookdefinition.
- Returns
The loaded AwsLambdaHook object.
- class Code[source]
Bases:
runway.lookups.handlers.base.LookupHandlerLookup for AwsLambdaHook responses.
- classmethod handle(value: str, context: Union[CfnginContext, RunwayContext], *args: Any, **kwargs: Any) Code[source]
Retrieve metadata for an AWS Lambda deployment package.
- Parameters
value – Value to resolve.
context – The current context object.
- Returns
Value that can be passed into CloudFormation property
AWS::Lambda::Function.Code.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
- class CodeSha256[source]
Bases:
runway.lookups.handlers.base.LookupHandlerLookup for AwsLambdaHook responses.
- classmethod handle(value: str, context: Union[CfnginContext, RunwayContext], *args: Any, **kwargs: Any) str[source]
Retrieve metadata for an AWS Lambda deployment package.
- Parameters
value – Value to resolve.
context – The current context object.
- Returns
Value that can be passed into CloudFormation property
AWS::Lambda::Version.CodeSha256.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
- class CompatibleArchitectures[source]
Bases:
runway.lookups.handlers.base.LookupHandlerLookup for AwsLambdaHook responses.
- classmethod handle(value: str, context: Union[CfnginContext, RunwayContext], *args: Any, **kwargs: Any) Optional[List[str]][source]
Retrieve metadata for an AWS Lambda deployment package.
- Parameters
value – Value to resolve.
context – The current context object.
- Returns
Value that can be passed into CloudFormation property
AWS::Lambda::LayerVersion.CompatibleArchitectures.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
- class CompatibleRuntimes[source]
Bases:
runway.lookups.handlers.base.LookupHandlerLookup for AwsLambdaHook responses.
- classmethod handle(value: str, context: Union[CfnginContext, RunwayContext], *args: Any, **kwargs: Any) Any[source]
Retrieve metadata for an AWS Lambda deployment package.
- Parameters
value – Value to resolve.
context – The current context object.
- Returns
Value that can be passed into CloudFormation property
AWS::Lambda::LayerVersion.CompatibleRuntimes.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
- class Content[source]
Bases:
runway.lookups.handlers.base.LookupHandlerLookup for AwsLambdaHook responses.
- classmethod handle(value: str, context: Union[CfnginContext, RunwayContext], *args: Any, **kwargs: Any) Content[source]
Retrieve metadata for an AWS Lambda deployment package.
- Parameters
value – Value to resolve.
context – The current context object.
- Returns
Value that can be passed into CloudFormation property
AWS::Lambda::LayerVersion.Content.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
- class LicenseInfo[source]
Bases:
runway.lookups.handlers.base.LookupHandlerLookup for AwsLambdaHook responses.
- classmethod handle(value: str, context: Union[CfnginContext, RunwayContext], *args: Any, **kwargs: Any) Optional[str][source]
Retrieve metadata for an AWS Lambda deployment package.
- Parameters
value – Value to resolve.
context – The current context object.
- Returns
Value that can be passed into CloudFormation property
AWS::Lambda::LayerVersion.LicenseInfo.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
- class Runtime[source]
Bases:
runway.lookups.handlers.base.LookupHandlerLookup for AwsLambdaHook responses.
- classmethod handle(value: str, context: Union[CfnginContext, RunwayContext], *args: Any, **kwargs: Any) str[source]
Retrieve metadata for an AWS Lambda deployment package.
- Parameters
value – Value to resolve.
context – The current context object.
- Returns
Value that can be passed into CloudFormation property
AWS::Lambda::Function.Runtime.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
- class S3Bucket[source]
Bases:
runway.lookups.handlers.base.LookupHandlerLookup for AwsLambdaHook responses.
- classmethod handle(value: str, context: Union[CfnginContext, RunwayContext], *args: Any, **kwargs: Any) str[source]
Retrieve metadata for an AWS Lambda deployment package.
- Parameters
value – Value to resolve.
context – The current context object.
- Returns
Value that can be passed into CloudFormation property
AWS::Lambda::Function.Code.S3BucketorAWS::Lambda::LayerVersion.Content.S3Bucket.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
- class S3Key[source]
Bases:
runway.lookups.handlers.base.LookupHandlerLookup for AwsLambdaHook responses.
- classmethod handle(value: str, context: Union[CfnginContext, RunwayContext], *args: Any, **kwargs: Any) str[source]
Retrieve metadata for an AWS Lambda deployment package.
- Parameters
value – Value to resolve.
context – The current context object.
- Returns
Value that can be passed into CloudFormation property
AWS::Lambda::Function.Code.S3KeyorAWS::Lambda::LayerVersion.Content.S3Key.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
- class S3ObjectVersion[source]
Bases:
runway.lookups.handlers.base.LookupHandlerLookup for AwsLambdaHook responses.
- classmethod handle(value: str, context: Union[CfnginContext, RunwayContext], *args: Any, **kwargs: Any) Optional[str][source]
Retrieve metadata for an AWS Lambda deployment package.
- Parameters
value – Value to resolve.
context – The current context object.
- Returns
Value that can be passed into CloudFormation property
AWS::Lambda::Function.Code.S3ObjectVersionorAWS::Lambda::LayerVersion.Content.S3ObjectVersion.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
Lookup to provide a default value.
- class runway.cfngin.lookups.handlers.default.DefaultLookup[source]
Bases:
runway.lookups.handlers.base.LookupHandlerLookup to provide a default value.
- TYPE_NAME: Final[typing_extensions.Literal[default]] = 'default'
Name that the Lookup is registered as.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod handle(value: str, context: Optional[CfnginContext] = None, **_: Any) Any[source]
Use a value from the environment or fall back to a default value.
Allows defaults to be set at the config file level.
- Parameters
value – Parameter(s) given to this lookup.
<env_var>::<default value>context – Context instance.
Example
Groups: ${default app_security_groups::sg-12345,sg-67890}If
app_security_groupsis defined in the environment, its defined value will be returned. Otherwise,sg-12345,sg-67890will be the returned value.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
DynamoDB lookup.
- class runway.cfngin.lookups.handlers.dynamodb.ArgsDataModel[source]
Bases:
runway.utils.BaseModelArguments data model.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.cfngin.lookups.handlers.dynamodb.QueryDataModel[source]
Bases:
runway.utils.BaseModelArguments data model.
- attribute: str
The attribute to be returned by this lookup. Supports additional syntax to retrieve a nested value.
- property item_key: Dict[str, Dict[typing_extensions.Literal[B, N, S], Any]]
Value to pass to boto3
.get_item()call as theKeyargument.- Raises
ValueError – The value of
partition_key_valuedoesn’t match the required regex and so it can’t be parsed.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.cfngin.lookups.handlers.dynamodb.DynamodbLookup[source]
Bases:
runway.lookups.handlers.base.LookupHandlerDynamoDB lookup.
- TYPE_NAME: Final[typing_extensions.Literal[dynamodb]] = 'dynamodb'
Name that the Lookup is registered as.
- classmethod parse(value: str) Tuple[str, Dict[str, str]][source]
Parse the value passed to the lookup.
This overrides the default parsing to account for special requirements.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- Raises
ValueError – The value provided does not appear to contain the name of a DynamoDB Table. The name of a Table is required.
- classmethod parse_query(value: str) runway.cfngin.lookups.handlers.dynamodb.QueryDataModel[source]
Parse query string to extract. Does not support arguments in
value.- Raises
ValueError – The argument provided does not match the expected format defined with a regex pattern.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod handle(value: str, context: runway.context.CfnginContext, *_DynamodbLookup__args: Any, **_DynamodbLookup__kwargs: Any) Any[source]
Get a value from a DynamoDB table.
- Parameters
value – Parameter(s) given to this lookup.
[<region>:]<tablename>@<partitionkey>:<keyvalue>.<keyvalue>...context – Context instance.
- Raises
ValueError – The value provided to the lookup resulted in an error.
Note
The region is optional, and defaults to the environment’s
AWS_DEFAULT_REGIONif not specified.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
Environment variable lookup.
- class runway.cfngin.lookups.handlers.envvar.EnvvarLookup[source]
Bases:
runway.lookups.handlers.base.LookupHandlerEnvironment variable lookup.
- TYPE_NAME: Final[typing_extensions.Literal[envvar]] = 'envvar'
Name that the Lookup is registered as.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod handle(value: str, **_: Any) str[source]
Retrieve an environment variable.
- Parameters
value – Parameter(s) given to this lookup.
Example
# With CFNgin we would reference the environment variable like this: conf_key: ${envvar ENV_VAR_NAME}You can optionally store the value in a file, ie:
$ cat envvar_value.txt ENV_VAR_NAME
and reference it within CFNgin (NOTE: the path should be relative to the CFNgin config file):
conf_key: ${envvar file://envvar_value.txt} # Both of the above would resolve to conf_key: ENV_VALUE
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
File lookup.
- class runway.cfngin.lookups.handlers.file.ArgsDataModel[source]
Bases:
runway.utils.BaseModelArguments data model.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.cfngin.lookups.handlers.file.FileLookup[source]
Bases:
runway.lookups.handlers.base.LookupHandlerFile lookup.
- TYPE_NAME: Final[typing_extensions.Literal[file]] = 'file'
Name that the Lookup is registered as.
- classmethod parse(value: str) Tuple[str, Dict[str, str]][source]
Parse the value passed to the lookup.
This overrides the default parsing to account for special requirements.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- Raises
ValueError – The value provided does not match the expected regex.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
- runway.cfngin.lookups.handlers.file.parameterized_codec(raw: str, b64: typing_extensions.Literal[False] = False) troposphere.GenericHelperFn[source]
- runway.cfngin.lookups.handlers.file.parameterized_codec(raw: str, b64: typing_extensions.Literal[True] = False) troposphere.Base64
Parameterize a string, possibly encoding it as Base64 afterwards.
- Parameters
raw – String to be processed. Byte strings will be interpreted as UTF-8.
b64 – Whether to wrap the output in a Base64 CloudFormation call.
- Returns
Output to be included in a CloudFormation template.
- Return type
troposphere.AWSHelperFn
Hook data lookup.
- class runway.cfngin.lookups.handlers.hook_data.HookDataLookup[source]
Bases:
runway.lookups.handlers.base.LookupHandlerHook data lookup.
- TYPE_NAME: Final[typing_extensions.Literal[hook_data]] = 'hook_data'
Name that the Lookup is registered as.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod handle(value: str, context: runway.context.CfnginContext, **_: Any) Any[source]
Return the data from
hook_data.- Parameters
value – Parameter(s) given to this lookup.
context – Context instance.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
AWS KMS lookup.
- class runway.cfngin.lookups.handlers.kms.KmsLookup[source]
Bases:
runway.lookups.handlers.base.LookupHandlerAWS KMS lookup.
- TYPE_NAME: Final[typing_extensions.Literal[kms]] = 'kms'
Name that the Lookup is registered as.
- classmethod legacy_parse(value: str) Tuple[str, Dict[str, str]][source]
Retain support for legacy lookup syntax.
Format of value:
<region>@<encrypted-blob>
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod handle(value: str, context: runway.context.CfnginContext, **_: Any) str[source]
Decrypt the specified value with a master key in KMS.
- Parameters
value – Parameter(s) given to this lookup.
context – Context instance.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
AWS CloudFormation Output lookup.
- class runway.cfngin.lookups.handlers.output.OutputQuery[source]
Bases:
NamedTupleOutput query NamedTuple.
- __init__()
- static __new__(_cls, stack_name: str, output_name: str)
Create new instance of OutputQuery(stack_name, output_name)
- count(value, /)
Return number of occurrences of value.
- index(value, start=0, stop=9223372036854775807, /)
Return first index of value.
Raises ValueError if the value is not present.
- class runway.cfngin.lookups.handlers.output.OutputLookup[source]
Bases:
runway.lookups.handlers.base.LookupHandlerAWS CloudFormation Output lookup.
- TYPE_NAME: Final[typing_extensions.Literal[output]] = 'output'
Name that the Lookup is registered as.
- classmethod legacy_parse(value: str) Tuple[runway.cfngin.lookups.handlers.output.OutputQuery, Dict[str, str]][source]
Retain support for legacy lookup syntax.
- Format of value:
<relative-stack-name>::<OutputName>
- classmethod handle(value: str, context: runway.context.CfnginContext, **_: Any) str[source]
Fetch an output from the designated stack.
- Parameters
value – Parameter(s) given to this lookup.
<relative-stack-name>.<OutputName>context – Context instance.
- Returns
Output from the specified stack.
- Raises
OutputDoesNotExist – Output not found for Stack.
StackDoesNotExist – Stack not found for the name provided.
- classmethod dependencies(lookup_query: VariableValue) Set[str][source]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- Parameters
lookup_query – Parameter(s) given to this lookup.
- Returns
Stack names this lookup depends on.
- __init__()
- __new__(**kwargs)
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
- runway.cfngin.lookups.handlers.output.deconstruct(value: str) runway.cfngin.lookups.handlers.output.OutputQuery[source]
Deconstruct the value.
Handler for fetching outputs from a stack in the current namespace.
- class runway.cfngin.lookups.handlers.rxref.RxrefLookup[source]
Bases:
runway.lookups.handlers.base.LookupHandlerRxref lookup.
- TYPE_NAME: Final[typing_extensions.Literal[rxref]] = 'rxref'
Name that the Lookup is registered as.
- classmethod legacy_parse(value: str) Tuple[runway.cfngin.lookups.handlers.output.OutputQuery, Dict[str, str]][source]
Retain support for legacy lookup syntax.
- Format of value:
<relative-stack-name>::<OutputName>
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod handle(value: str, context: CfnginContext, provider: Provider, **_: Any) Any[source]
Fetch an output from the designated stack in the current namespace.
The
outputlookup supports fetching outputs from stacks created within a single config file. Sometimes it’s useful to fetch outputs from stacks created outside of the current config file but using the same namespace.rxrefsupports this by using therunway.context.CfnginContextto expand the fqn of the stack.- Parameters
value – Parameter(s) given to this lookup. “<relative-stack-name>.<OutputName>`
context – Context instance.
provider – Provider instance.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
Split lookup.
- class runway.cfngin.lookups.handlers.split.SplitLookup[source]
Bases:
runway.lookups.handlers.base.LookupHandlerSplit lookup.
- TYPE_NAME: Final[typing_extensions.Literal[split]] = 'split'
Name that the Lookup is registered as.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod handle(value: str, **_: Any) List[str][source]
Split the supplied string on the given delimiter, providing a list.
- Parameters
value – Parameter(s) given to this lookup.
Format of value:
<delimiter>::<value>
Example
Subnets: ${split ,::subnet-1,subnet-2,subnet-3}Would result in the variable Subnets getting a list consisting of:
["subnet-1", "subnet-2", "subnet-3"]
This is particularly useful when getting an output from another stack that contains a list. For example, the standard vpc blueprint outputs the list of Subnets it creates as a pair of Outputs (
PublicSubnets,PrivateSubnets) that are comma separated, so you could use this in your config:Subnets: ${split ,::${output vpc.PrivateSubnets}}
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
Handler for fetching outputs from fully qualified stacks.
- class runway.cfngin.lookups.handlers.xref.XrefLookup[source]
Bases:
runway.lookups.handlers.base.LookupHandlerXref lookup.
- TYPE_NAME: Final[typing_extensions.Literal[xref]] = 'xref'
Name that the Lookup is registered as.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod handle(value: str, provider: Provider, **_: Any) str[source]
Fetch an output from the designated, fully qualified stack.
The output handler supports fetching outputs from stacks created within a single config file. Sometimes it’s useful to fetch outputs from stacks created outside of the current config file. xref supports this by not using the
runway.context.CfnginContextto expand the fqn of the stack.- Parameters
value – Parameter(s) given to this lookup.
<stack_name>::<output_name>provider – Provider instance.
- Returns
Output from the specified stack.
Example
conf_value: ${xref fully-qualified-stack-name::SomeOutputName}
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
CFNgin lookup registry.
- runway.cfngin.lookups.registry.register_lookup_handler(lookup_type: str, handler_or_path: Union[str, Type[runway.lookups.handlers.base.LookupHandler]]) None[source]
Register a lookup handler.
- Parameters
lookup_type – Name to register the handler under.
handler_or_path – A function or a path to a handler.
- runway.cfngin.lookups.registry.unregister_lookup_handler(lookup_type: str) None[source]
Unregister the specified lookup type.
This is useful when testing various lookup types if you want to unregister the lookup type after the test runs.
- Parameters
lookup_type – Name of the lookup type to unregister.
Import modules.
Import modules.
Default AWS Provider.
- runway.cfngin.providers.aws.default.get_cloudformation_client(session: boto3.Session) CloudFormationClient[source]
Get CloudFormation boto3 client.
- runway.cfngin.providers.aws.default.get_output_dict(stack: StackTypeDef) Dict[str, str][source]
Return a dict of key/values for the outputs for a given CF stack.
- Parameters
stack – The stack object to get outputs from.
- Returns
A dictionary with key/values for each output on the stack.
- runway.cfngin.providers.aws.default.s3_fallback(fqn: str, template: Template, parameters: List[ParameterTypeDef], tags: List[TagTypeDef], method: Callable[..., Any], change_set_name: Optional[str] = None, service_role: Optional[str] = None) Any[source]
Falling back to legacy CFNgin S3 bucket region for templates.
- runway.cfngin.providers.aws.default.get_change_set_name() str[source]
Return a valid Change Set Name.
The name has to satisfy the following regex:
[a-zA-Z][-a-zA-Z0-9]*
And must be unique across all change sets.
- runway.cfngin.providers.aws.default.requires_replacement(changeset: List[ChangeTypeDef]) List[ChangeTypeDef][source]
Return the changes within the changeset that require replacement.
- Parameters
changeset – List of changes
- runway.cfngin.providers.aws.default.output_full_changeset(full_changeset: Optional[List[ChangeTypeDef]] = None, params_diff: Optional[List[DictValue[Any, Any]]] = None, answer: Optional[str] = None, fqn: Optional[str] = None) None[source]
Optionally output full changeset.
- Parameters
full_changeset – A list of the full changeset that will be output if the user specifies verbose.
params_diff – A list of DictValue detailing the differences between two parameters returned by
runway.cfngin.actions.diff.diff_dictionaries().answer – Predetermined answer to the prompt if it has already been answered or inferred.
fqn – Fully qualified name of the stack.
- runway.cfngin.providers.aws.default.ask_for_approval(full_changeset: Optional[List[ChangeTypeDef]] = None, params_diff: Optional[List[DictValue[Any, Any]]] = None, include_verbose: bool = False, fqn: Optional[str] = None) None[source]
Prompt the user for approval to execute a change set.
- Parameters
full_changeset – A list of the full changeset that will be output if the user specifies verbose.
params_diff – A list of DictValue detailing the differences between two parameters returned by
runway.cfngin.actions.diff.diff_dictionaries()include_verbose – Boolean for whether or not to include the verbose option.
fqn – fully qualified name of the stack.
- Raises
CancelExecution – If approval no given.
- runway.cfngin.providers.aws.default.output_summary(fqn: str, action: str, changeset: List[ChangeTypeDef], params_diff: List[DictValue[Any, Any]], replacements_only: bool = False) None[source]
Log a summary of the changeset.
- Parameters
fqn – Fully qualified name of the stack.
action – Action to include in the log message.
changeset – AWS changeset.
params_diff – A list of dictionaries detailing the differences between two parameters returned by
runway.cfngin.actions.diff.diff_dictionaries()replacements_only – Boolean for whether or not we only want to list replacements.
- runway.cfngin.providers.aws.default.format_params_diff(params_diff: List[runway.cfngin.actions.diff.DictValue[Any, Any]]) str[source]
Wrap
runway.cfngin.actions.diff.format_params_diff()for testing.
- runway.cfngin.providers.aws.default.summarize_params_diff(params_diff: List[runway.cfngin.actions.diff.DictValue[Any, Any]]) str[source]
Summarize parameter diff.
- runway.cfngin.providers.aws.default.wait_till_change_set_complete(cfn_client: CloudFormationClient, change_set_id: str, try_count: int = 25, sleep_time: float = 0.5, max_sleep: float = 3) DescribeChangeSetOutputTypeDef[source]
Check state of a changeset, returning when it is in a complete state.
Since changesets can take a little bit of time to get into a complete state, we need to poll it until it does so. This will try to get the state
try_counttimes, waitingsleep_time* 2 seconds between each try up to themax_sleepnumber of seconds. If, after that time, the changeset is not in a complete state it fails. These default settings will wait a little over one minute.- Parameters
cfn_client – Used to query CloudFormation.
change_set_id – The unique changeset id to wait for.
try_count – Number of times to try the call.
sleep_time – Time to sleep between attempts.
max_sleep – Max time to sleep during backoff
- runway.cfngin.providers.aws.default.create_change_set(cfn_client: CloudFormationClient, fqn: str, template: Template, parameters: List[ParameterTypeDef], tags: List[TagTypeDef], change_set_type: str = 'UPDATE', service_role: Optional[str] = None) Tuple[List[ChangeTypeDef], str][source]
Create CloudFormation change set.
- runway.cfngin.providers.aws.default.check_tags_contain(actual: List[TagTypeDef], expected: List[TagTypeDef]) bool[source]
Check if a set of AWS resource tags is contained in another.
Every tag key in
expectedmust be present inactual, and have the same value. Extra keys in actual but not inexpectedare ignored.- Parameters
actual – Set of tags to be verified, usually from the description of a resource. Each item must be a
dictcontainingKeyandValueitems.expected – Set of tags that must be present in
actual(in the same format).
- runway.cfngin.providers.aws.default.generate_cloudformation_args(stack_name: str, parameters: List[ParameterTypeDef], tags: List[TagTypeDef], template: Template, capabilities: Optional[List[str]] = None, change_set_type: Optional[str] = None, service_role: Optional[str] = None, stack_policy: Optional[Template] = None, change_set_name: Optional[str] = None) Dict[str, Any][source]
Generate the args for common CloudFormation API interactions.
This is used for
create_stack/update_stack/create_change_setcalls in CloudFormation.- Parameters
stack_name – The fully qualified stack name in Cloudformation.
parameters – A list of dictionaries that defines the parameter list to be applied to the Cloudformation stack.
tags – A list of dictionaries that defines the tags that should be applied to the Cloudformation stack.
template – The template object.
capabilities – A list of capabilities to use when updating Cloudformation.
change_set_type – An optional change set type to use with create_change_set.
service_role – An optional service role to use when interacting with Cloudformation.
stack_policy – A template object representing a stack policy.
change_set_name – An optional change set name to use with create_change_set.
- runway.cfngin.providers.aws.default.generate_stack_policy_args(stack_policy: Optional[Template] = None) Dict[str, str][source]
Convert a stack policy object into keyword args.
- Parameters
stack_policy – A template object representing a stack policy.
- class runway.cfngin.providers.aws.default.ProviderBuilder[source]
Bases:
objectImplements a Memorized ProviderBuilder for the AWS provider.
- build(*, profile: Optional[str] = None, region: Optional[str] = None) runway.cfngin.providers.aws.default.Provider[source]
Get or create the provider for the given region and profile.
- __new__(**kwargs)
- class runway.cfngin.providers.aws.default.Provider[source]
Bases:
runway.cfngin.providers.base.BaseProviderAWS CloudFormation Provider.
- __init__(session: boto3.Session, *, interactive: bool = False, recreate_failed: bool = False, region: Optional[str] = None, replacements_only: bool = False, service_role: Optional[str] = None)[source]
Instantiate class.
- static get_stack_status(stack: StackTypeDef, *_args: Any, **_kwargs: Any) str[source]
Get stack status.
- is_stack_being_destroyed(stack: StackTypeDef) bool[source]
Whether the status of the stack indicates it is ‘being destroyed’.
- is_stack_completed(stack: StackTypeDef) bool[source]
Whether the status of the stack indicates it is ‘complete’.
- is_stack_destroy_possible(stack: StackTypeDef) bool[source]
Whether the status of the stack is able to be cleanly deleted.
- is_stack_in_progress(stack: StackTypeDef) bool[source]
Whether the status of the stack indicates it is ‘in progress’.
- is_stack_destroyed(stack: StackTypeDef) bool[source]
Whether the status of the stack indicates it is ‘deleted’.
- is_stack_recreatable(stack: StackTypeDef) bool[source]
Whether the status of the stack indicates it is ‘recreating’.
- is_stack_rolling_back(stack: StackTypeDef) bool[source]
Whether the status of the stack indicates it is ‘rolling back’.
- is_stack_failed(stack: StackTypeDef) bool[source]
Whether the status of the stack indicates it is ‘failed’.
- is_stack_in_review(stack: StackTypeDef) bool[source]
Whether the status of the stack indicates if ‘review in progress’.
- tail_stack(stack: Stack, cancel: threading.Event, action: Optional[str] = None, log_func: Optional[Callable[[StackEventTypeDef], None]] = None, retries: Optional[int] = None) None[source]
Tail the events of a stack.
- get_delete_failed_status_reason(stack_name: str) Optional[str][source]
Process events and return latest delete failed reason.
- Parameters
stack_name – Name of a CloudFormation Stack.
- Returns
Reason for the Stack’s DELETE_FAILED status if one can be found.
- get_event_by_resource_status(stack_name: str, status: str, *, chronological: bool = True) Optional[StackEventTypeDef][source]
Get Stack Event of a given set of resource status.
- Parameters
stack_name – Name of a CloudFormation Stack.
status – Resource status to look for.
chronological – Whether to sort events in chronological order before looking for the desired status.
- Returns
The first Stack Event matching the given status.
- get_events(stack_name: str, chronological: bool = True) Iterable[StackEventTypeDef][source]
Get the events in batches and return in chronological order.
- get_rollback_status_reason(stack_name: str) Optional[str][source]
Process events and returns latest roll back reason.
- Parameters
stack_name – Name of a CloudFormation Stack.
- Returns
Reason for the Stack’s rollback status if one can be found.
- tail(stack_name: str, cancel: threading.Event, log_func: Callable[[StackEventTypeDef], None] = <staticmethod object>, sleep_time: int = 5, include_initial: bool = True) None[source]
Show and then tail the event log.
- destroy_stack(stack: StackTypeDef, *, action: str = 'destroy', approval: Optional[str] = None, force_interactive: bool = False, **kwargs: Any) None[source]
Destroy a CloudFormation Stack.
- Parameters
stack – Stack to be destroyed.
action – Name of the action being executed. This impacts the log message used.
approval – Response to approval prompt.
force_interactive – Always ask for approval.
- create_stack(fqn: str, template: Template, parameters: List[ParameterTypeDef], tags: List[TagTypeDef], *, force_change_set: bool = False, stack_policy: Optional[Template] = None, termination_protection: bool = False, timeout: Optional[int] = None, **kwargs: Any) None[source]
Create a new Cloudformation stack.
- Parameters
fqn – The fully qualified name of the Cloudformation stack.
template – A Template object to use when creating the stack.
parameters – A list of dictionaries that defines the parameter list to be applied to the Cloudformation stack.
tags – A list of dictionaries that defines the tags that should be applied to the Cloudformation stack.
force_change_set – Whether or not to force change set use.
stack_policy – A template object representing a stack policy.
termination_protection – End state of the stack’s termination protection.
timeout – The amount of time that can pass before the stack status becomes
CREATE_FAILED.
- select_update_method(force_interactive: bool, force_change_set: bool) Callable[[...], None][source]
Select the correct update method when updating a stack.
- Parameters
force_interactive – Whether or not to force interactive mode no matter what mode the provider is in.
force_change_set – Whether or not to force change set use.
- Returns
The correct object method to use when updating.
- Return type
function
- prepare_stack_for_update(stack: StackTypeDef, tags: List[TagTypeDef]) bool[source]
Prepare a stack for updating.
It may involve deleting the stack if is has failed it’s initial creation. The deletion is only allowed if:
The stack contains all the tags configured in the current context;
The stack is in one of the statuses considered safe to re-create
recreate_failedis enabled, due to either being explicitly enabled by the user, or because interactive mode is on.
- Parameters
stack – A stack object returned from get_stack
tags – List of expected tags that must be present in the stack if it must be re-created
- Returns
True if the stack can be updated, False if it must be re-created
- update_stack(fqn: str, template: Template, old_parameters: List[ParameterTypeDef], parameters: List[ParameterTypeDef], tags: List[TagTypeDef], force_interactive: bool = False, force_change_set: bool = False, stack_policy: Optional[Template] = None, termination_protection: bool = False, **kwargs: Any) None[source]
Update a Cloudformation stack.
- Parameters
fqn – The fully qualified name of the Cloudformation stack.
template – A Template object to use when updating the stack.
old_parameters – A list of dictionaries that defines the parameter list on the existing Cloudformation stack.
parameters – A list of dictionaries that defines the parameter list to be applied to the Cloudformation stack.
tags – A list of dictionaries that defines the tags that should be applied to the Cloudformation stack.
force_interactive – A flag that indicates whether the update should be interactive. If set to True, interactive mode will be used no matter if the provider is in interactive mode or not. False will follow the behavior of the provider.
force_change_set – A flag that indicates whether the update must be executed with a change set.
stack_policy – A template object representing a stack policy.
termination_protection – End state of the stack’s termination protection.
- update_termination_protection(fqn: str, termination_protection: bool) None[source]
Update a Stack’s termination protection if needed.
Runs before the normal stack update process.
- Parameters
fqn – The fully qualified name of the Cloudformation stack.
termination_protection – End state of the stack’s termination protection.
- deal_with_changeset_stack_policy(fqn: str, stack_policy: Optional[Template] = None) None[source]
Set a stack policy when using changesets.
ChangeSets don’t allow you to set stack policies in the same call to update them. This sets it before executing the changeset if the stack policy is passed in.
- Parameters
fqn – Fully qualified name of the stack.
stack_policy – A template object representing a stack policy.
- interactive_destroy_stack(fqn: str, approval: Optional[str] = None, **kwargs: Any) None[source]
Delete a CloudFormation stack in interactive mode.
- Parameters
fqn – A fully qualified stack name.
approval – Response to approval prompt.
- interactive_update_stack(fqn: str, template: Template, old_parameters: List[ParameterTypeDef], parameters: List[ParameterTypeDef], stack_policy: Template, tags: List[TagTypeDef]) None[source]
Update a Cloudformation stack in interactive mode.
- Parameters
fqn – The fully qualified name of the Cloudformation stack.
template – A Template object to use when updating the stack.
old_parameters – A list of dictionaries that defines the parameter list on the existing Cloudformation stack.
parameters – A list of dictionaries that defines the parameter list to be applied to the Cloudformation stack.
stack_policy – A template object representing a stack policy.
tags – A list of dictionaries that defines the tags that should be applied to the Cloudformation stack.
- noninteractive_destroy_stack(fqn: str, **_kwargs: Any) None[source]
Delete a CloudFormation stack without interaction.
- Parameters
fqn – A fully qualified stack name.
- __new__(**kwargs)
- noninteractive_changeset_update(fqn: str, template: Template, old_parameters: List[ParameterTypeDef], parameters: List[ParameterTypeDef], stack_policy: Optional[Template], tags: List[TagTypeDef]) None[source]
Update a Cloudformation stack using a change set.
This is required for stacks with a defined Transform (i.e. SAM), as the default
update_stackAPI cannot be used with them.- Parameters
fqn – The fully qualified name of the Cloudformation stack.
template – A Template object to use when updating the stack.
old_parameters – A list of dictionaries that defines the parameter list on the existing Cloudformation stack.
parameters – A list of dictionaries that defines the parameter list to be applied to the Cloudformation stack.
stack_policy – A template object representing a stack policy.
tags – A list of dictionaries that defines the tags that should be applied to the Cloudformation stack.
- select_destroy_method(force_interactive: bool) Callable[[...], None][source]
Select the correct destroy method for destroying a stack.
- Parameters
force_interactive – Always ask for approval.
- Returns
Interactive or non-interactive method to be invoked.
- default_update_stack(fqn: str, template: Template, old_parameters: List[ParameterTypeDef], parameters: List[ParameterTypeDef], tags: List[TagTypeDef], stack_policy: Optional[Template] = None) None[source]
Update a Cloudformation stack in default mode.
- Parameters
fqn – The fully qualified name of the Cloudformation stack.
template – A Template object to use when updating the stack.
old_parameters – A list of dictionaries that defines the parameter list on the existing Cloudformation stack.
parameters – A list of dictionaries that defines the parameter list to be applied to the Cloudformation stack.
tags – A list of dictionaries that defines the tags that should be applied to the Cloudformation stack.
stack_policy – A template object representing a stack policy.
- static get_stack_tags(stack: StackTypeDef) List[TagTypeDef][source]
Get stack tags.
- get_outputs(stack_name: str, *_args: Any, **_kwargs: Any) Dict[str, str][source]
Get stack outputs.
- get_stack_info(stack: StackTypeDef) Tuple[str, Dict[str, Union[List[str], str]]][source]
Get the template and parameters of the stack currently in AWS.
- get_stack_changes(stack: Stack, template: Template, parameters: List[ParameterTypeDef], tags: List[TagTypeDef]) Dict[str, str][source]
Get the changes from a ChangeSet.
- Parameters
stack – The stack to get changes.
template – A Template object to compared to.
parameters – A list of dictionaries that defines the parameter list to be applied to the Cloudformation stack.
tags – A list of dictionaries that defines the tags that should be applied to the Cloudformation stack.
- Returns
Stack outputs with inferred changes.
Provider base class.
- runway.cfngin.providers.base.not_implemented(method: str) None[source]
Wrap NotImplimentedError with a formatted message.
- class runway.cfngin.providers.base.BaseProviderBuilder[source]
Bases:
objectProviderBuilder base class.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.providers.base.BaseProvider[source]
Bases:
objectProvider base class.
- __init__()
- __new__(**kwargs)
- class runway.cfngin.providers.base.Template[source]
Bases:
objectCloudFormation stack template, which could be optionally uploaded to s3.
Presence of the url attribute indicates that the template was uploaded to S3, and the uploaded template should be used for
CreateStack/UpdateStackcalls.- __new__(**kwargs)
Copy of awscli.customizations.cloudformation.yamlhelper.py.
- runway.cfngin.awscli_yamlhelper.intrinsics_multi_constructor(loader: yaml.loader.Loader, tag_prefix: str, node: yaml.nodes.Node) Dict[str, Any][source]
YAML constructor to parse CloudFormation intrinsics.
This will return a dictionary with key being the intrinsic name
CFNgin entrypoint.
- class runway.cfngin.cfngin.CFNgin[source]
Bases:
objectControl CFNgin.
- concurrency
Max number of CFNgin stacks that can be deployed concurrently. If the value is
0, will be constrained based on the underlying graph.- Type
- parameters
Combination of the parameters provided when initializing the class and any environment files that are found.
- recreate_failed
Destroy and re-create stacks that are stuck in a failed state from an initial deployment when updating.
- Type
- sys_path
Working directory.
- Type
- __init__(ctx: runway.context.RunwayContext, parameters: Optional[Dict[str, Any]] = None, sys_path: Optional[pathlib.Path] = None) None[source]
Instantiate class.
- Parameters
ctx – Runway context object.
parameters – Parameters from Runway.
sys_path – Working directory.
- property env_file: runway.utils.MutableMap
Contents of a CFNgin environment file.
- deploy(force: bool = False, sys_path: Optional[pathlib.Path] = None) None[source]
Run the CFNgin deploy action.
- Parameters
force – Explicitly enable the action even if an environment file is not found.
sys_path – Explicitly define a path to work in. If not provided,
self.sys_pathis used.
- destroy(force: bool = False, sys_path: Optional[pathlib.Path] = None) None[source]
Run the CFNgin destroy action.
- Parameters
force – Explicitly enable the action even if an environment file is not found.
sys_path – Explicitly define a path to work in. If not provided,
self.sys_pathis used.
- init(force: bool = False, sys_path: Optional[pathlib.Path] = None) None[source]
Initialize environment.
- load(config_path: pathlib.Path) runway.context.CfnginContext[source]
Load a CFNgin config into a context object.
- Parameters
config_path – Valid path to a CFNgin config file.
- __new__(**kwargs)
- plan(force: bool = False, sys_path: Optional[pathlib.Path] = None)[source]
Run the CFNgin plan action.
- Parameters
force – Explicitly enable the action even if an environment file is not found.
sys_path – Explicitly define a path to work in. If not provided,
self.sys_pathis used.
- should_skip(force: bool = False) bool[source]
Determine if action should be taken or not.
- Parameters
force – If
True, will always returnFalsemeaning the action should not be skipped.
- classmethod find_config_files(exclude: Optional[List[str]] = None, sys_path: Optional[pathlib.Path] = None) List[pathlib.Path][source]
Find CFNgin config files.
- Parameters
exclude – List of file names to exclude. This list is appended to the global exclude list.
sys_path – Explicitly define a path to search for config files.
- Returns
Paths to config files that were found.
CFNgin environment file parsing.
CFNgin exceptions.
- exception runway.cfngin.exceptions.CfnginError[source]
Bases:
runway.exceptions.RunwayErrorBase class for custom exceptions raised by Runway.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.CancelExecution[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when we want to cancel executing the plan.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.CfnginBucketAccessDenied[source]
Bases:
runway.cfngin.exceptions.CfnginErrorAccess denied to CFNgin bucket.
This can occur when the bucket exists in another AWS account and/or the credentials being used do not have adequate permissions to access the bucket.
- __init__(*, bucket_name: str) None[source]
Instantiate class.
- Parameters
bucket_name – Name of the CFNgin bucket.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.CfnginBucketNotFound[source]
Bases:
runway.cfngin.exceptions.CfnginErrorCFNgin bucket specified or default bucket being used but it does not exist.
This can occur when using a custom stack to deploy the CFNgin bucket but the custom stack does not create bucket that is expected.
- __init__(*, bucket_name: str) None[source]
Instantiate class.
- Parameters
bucket_name – Name of the CFNgin bucket.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.CfnginBucketRequired[source]
Bases:
runway.cfngin.exceptions.CfnginErrorCFNgin bucket is required to use a feature but it not provided/disabled.
- __init__(*, config_path: Optional[AnyPath] = None, reason: Optional[str] = None) None[source]
Instantiate class.
- Parameters
config_path – Path to the CFNgin config file.
reason – Reason why CFNgin bucket is needed.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.CfnginOnlyLookupError[source]
Bases:
runway.cfngin.exceptions.CfnginErrorAttempted to use a CFNgin lookup outside of CFNgin.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.ChangesetDidNotStabilize[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when the applying a changeset fails.
- __init__(change_set_id: str) None[source]
Instantiate class.
- Parameters
change_set_id – The changeset that failed.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.GraphError[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when the graph is invalid (e.g. acyclic dependencies).
- __init__(exception: Exception, stack: str, dependency: str) None[source]
Instantiate class.
- Parameters
exception – The exception that was raised by the invalid graph.
stack – Name of the stack causing the error.
dependency – Name of the dependency causing the error.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.ImproperlyConfigured[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when a component is improperly configured.
- __init__(kls: Any, error: Exception, *args: Any, **kwargs: Any) None[source]
Instantiate class.
- Parameters
kls – The class that was improperly configured.
error – The exception that was raised when trying to use cls.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.InvalidConfig[source]
Bases:
runway.cfngin.exceptions.CfnginErrorProvided config file is invalid.
- __init__(errors: Union[str, List[Union[Exception, str]]]) None[source]
Instantiate class.
- Parameters
errors – Errors or error messages that are raised to identify that a config is invalid.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.InvalidDockerizePipConfiguration[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when the provided configuration for dockerized pip is invalid.
- __init__(msg: str) None[source]
Instantiate class.
- Parameters
msg – The reason for the error being raised.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.InvalidUserdataPlaceholder[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when a placeholder name in raw_user_data is not valid.
E.g
${100}would raise this.- __init__(blueprint_name: str, exception_message: str, *args: Any, **kwargs: Any) None[source]
Instantiate class.
- Parameters
blueprint_name – Name of the blueprint with invalid userdata placeholder.
exception_message – Message from the exception that was raised while parsing the userdata.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.MissingEnvironment[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when an environment lookup is used but the key doesn’t exist.
- __init__(key: str, *args: Any, **kwargs: Any) None[source]
Instantiate class.
- Parameters
key – The key that was used but doesn’t exist in the environment.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.MissingParameterException[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised if a required parameter with no default is missing.
- __init__(parameters: List[str], *args: Any, **kwargs: Any) None[source]
Instantiate class.
- Parameters
parameters – A list of the parameters that are missing.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.MissingVariable[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when a variable with no default is not provided a value.
- __init__(blueprint_name: str, variable_name: str, *args: Any, **kwargs: Any) None[source]
Instantiate class.
- Parameters
blueprint_name – Name of the blueprint.
variable_name – Name of the variable missing a value.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.PipError[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when pip returns a non-zero exit code.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.PipenvError[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when pipenv returns a non-zero exit code.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.PersistentGraphCannotLock[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when the persistent graph in S3 cannot be locked.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.PersistentGraphCannotUnlock[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when the persistent graph in S3 cannot be unlocked.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.PersistentGraphLocked[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when the persistent graph in S3 is lock.
The action being executed requires it to be unlocked before attempted.
- __init__(*, message: Optional[str] = None, reason: Optional[str] = None) None[source]
Instantiate class.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.PersistentGraphLockCodeMismatch[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when the provided persistent graph lock code does not match.
The code used to unlock the persistent graph must match the s3 object lock code.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.PersistentGraphUnlocked[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when the persistent graph in S3 is unlock.
The action being executed requires it to be locked before attempted.
- __init__(message: Optional[str] = None, reason: Optional[str] = None) None[source]
Instantiate class.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.PlanFailed[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised if any step of a plan fails.
- __init__(failed_steps: List[Step], *args: Any, **kwargs: Any) None[source]
Instantiate class.
- Parameters
failed_steps – The steps that failed.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.StackDidNotChange[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when there are no changes to be made by the provider.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.StackDoesNotExist[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when a stack does not exist in AWS.
- __init__(stack_name: str, *args: Any, **kwargs: Any) None[source]
Instantiate class.
- Parameters
stack_name – Name of the stack that does not exist.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.StackUpdateBadStatus[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised if the state of a stack can’t be handled.
- __init__(stack_name: str, stack_status: str, reason: str, *args: Any, **kwargs: Any) None[source]
Instantiate class.
- Parameters
stack_name – Name of the stack.
stack_status – The stack’s status.
reason – The reason for the current status.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.StackFailed[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when a stack action fails.
Primarily used with hooks that act on stacks.
- __init__(stack_name: str, status_reason: Optional[str] = None) None[source]
Instantiate class.
- Parameters
stack_name – Name of the stack.
status_reason – The reason for the current status.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.UnableToExecuteChangeSet[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised if changeset execution status is not
AVAILABLE.- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.UnhandledChangeSetStatus[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when creating a changeset failed for an unhandled reason.
Handled failure reasons include: no changes
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.UnresolvedBlueprintVariable[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when trying to use a variable before it has been resolved.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.UnresolvedBlueprintVariables[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when trying to use variables before they has been resolved.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.cfngin.exceptions.ValidatorError[source]
Bases:
runway.cfngin.exceptions.CfnginErrorUsed for errors raised by custom validators of blueprint variables.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- __init__(variable: str, validator: str, value: str, exception: Optional[Exception] = None) None[source]
Instantiate class.
- Parameters
variable – The variable that failed validation.
validator – The validator that was not passed.
value – The value of the variable that did not pass the validator.
exception – The exception raised by the validator.
- exception runway.cfngin.exceptions.VariableTypeRequired[source]
Bases:
runway.cfngin.exceptions.CfnginErrorRaised when a variable defined in a blueprint is missing a type.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
CFNgin plan, plan components, and functions for interacting with a plan.
- runway.cfngin.plan.json_serial(obj: Set[runway.cfngin.plan._T]) List[runway.cfngin.plan._T][source]
- runway.cfngin.plan.json_serial(obj: Union[Dict[Any, Any], int, List[Any], str]) NoReturn
Serialize json.
- Parameters
obj – A python object.
Example
json.dumps(data, default=json_serial)
- runway.cfngin.plan.merge_graphs(graph1: runway.cfngin.plan.Graph, graph2: runway.cfngin.plan.Graph) runway.cfngin.plan.Graph[source]
Combine two Graphs into one, retaining steps.
- Parameters
graph1 – Graph that
graph2will be merged into.graph2 – Graph that will be merged into
graph1.
- class runway.cfngin.plan.Step[source]
Bases:
objectState machine for executing generic actions related to stacks.
- fn
Function to run to execute the step. This function will be ran multiple times until the step is “done”.
- Type
Optional[Callable[…, Any]]
- logger
Logger for logging messages about the step.
- Type
PrefixAdaptor
- watch_func
Function that will be called to “tail” the step action.
- Type
Optional[Callable[…, Any]]
- __init__(stack: runway.cfngin.stack.Stack, *, fn: Optional[Callable[[...], Any]] = None, watch_func: Optional[Callable[[...], Any]] = None) None[source]
Instantiate class.
- Parameters
stack – The stack associated with this step
fn – Function to run to execute the step. This function will be ran multiple times until the step is “done”.
watch_func – Function that will be called to “tail” the step action.
- property done: bool
Return True if the step is finished.
To be
True, status must be either COMPLETE, SKIPPED or FAILED)
- set_status(status: Status) None[source]
Set the current step’s status.
- Parameters
status – The status to set the step to.
- classmethod from_stack_name(stack_name: str, context: CfnginContext, requires: Optional[Union[List[str], Set[str]]] = None, fn: Optional[Callable[..., Status]] = None, watch_func: Optional[Callable[..., Any]] = None) Step[source]
Create a step using only a stack name.
- Parameters
stack_name – Name of a CloudFormation stack.
context – Context object. Required to initialize a “fake”
runway.cfngin.stack.Stack.requires – Stacks that this stack depends on.
fn – The function to run to execute the step. This function will be ran multiple times until the step is “done”.
watch_func – an optional function that will be called to “tail” the step action.
- classmethod from_persistent_graph(graph_dict: Union[Dict[str, List[str]], Dict[str, Set[str]], OrderedDict[str, Set[str]]], context: CfnginContext, fn: Optional[Callable[..., Status]] = None, watch_func: Optional[Callable[..., Any]] = None) List[Step][source]
Create a steps for a persistent graph dict.
- Parameters
graph_dict – A graph dict.
context – Context object. Required to initialize a “fake”
runway.cfngin.stack.Stack.requires – Stacks that this stack depends on.
fn – The function to run to execute the step. This function will be ran multiple times until the step is “done”.
watch_func – an optional function that will be called to “tail” the step action.
- __new__(**kwargs)
- class runway.cfngin.plan.Graph[source]
Bases:
objectGraph represents a graph of steps.
The
Graphhelps organize the steps needed to execute a particular action for a set ofrunway.cfngin.stack.Stackobjects. When initialized with a set of steps, it will first build a Directed Acyclic Graph from the steps and their dependencies.Example
>>> dag = DAG() >>> a = Step("a", fn=deploy) >>> b = Step("b", fn=deploy) >>> dag.add_step(a) >>> dag.add_step(b) >>> dag.connect(a, b)
- __init__(steps: Optional[Dict[str, runway.cfngin.plan.Step]] = None, dag: Optional[runway.cfngin.dag.DAG] = None) None[source]
Instantiate class.
- Parameters
steps – Dict with key of step name and value of
Stepfor steps to initialize the Graph with. Note that if this is provided, a pre-configuredrunway.cfngin.dag.DAGthat already includes these steps should also be provided..dag – An optional
runway.cfngin.dag.DAGobject. If one is not provided, a new one will be initialized.
- add_step(step: runway.cfngin.plan.Step, add_dependencies: bool = False, add_dependents: bool = False) None[source]
Add a step to the graph.
- Parameters
step – The step to be added.
add_dependencies – Connect steps that need to be completed before this step.
add_dependents – Connect steps that require this step.
- add_step_if_not_exists(step: runway.cfngin.plan.Step, add_dependencies: bool = False, add_dependents: bool = False) None[source]
Try to add a step to the graph.
Can be used when failure to add is acceptable.
- Parameters
step – The step to be added.
add_dependencies – Connect steps that need to be completed before this step.
add_dependents – Connect steps that require this step.
- add_steps(steps: List[runway.cfngin.plan.Step]) None[source]
Add a list of steps.
- Parameters
steps – The step to be added.
- pop(step: runway.cfngin.plan.Step, default: Optional[Any] = None) Any[source]
Remove a step from the graph.
- Parameters
step – The step to remove from the graph.
default – Returned if the step could not be popped
- connect(step: str, dep: str) None[source]
Connect a dependency to a step.
- Parameters
step – Step name to add a dependency to.
dep – Name of dependent step.
- transitive_reduction() None[source]
Perform a transitive reduction on the underlying DAG.
The transitive reduction of a graph is a graph with as few edges as possible with the same reachability as the original graph.
- walk(walker: Callable[[runway.cfngin.dag.DAG, Callable[[str], Any]], Any], walk_func: Callable[[runway.cfngin.plan.Step], Any]) Any[source]
Walk the steps of the graph.
- Parameters
walker – Function used to walk the steps.
walk_func – Function called with a
Stepas the only argument for each step of the plan.
- downstream(step_name: str) List[runway.cfngin.plan.Step][source]
Return the direct dependencies of the given step.
- transposed() runway.cfngin.plan.Graph[source]
Return a “transposed” version of this graph.
Useful for walking in reverse.
- filtered(step_names: List[str]) runway.cfngin.plan.Graph[source]
Return a “filtered” version of this graph.
- Parameters
step_names – Steps to filter.
- topological_sort() List[runway.cfngin.plan.Step][source]
Perform a topological sort of the underlying DAG.
- dumps(indent: Optional[int] = None) str[source]
Output the graph as a json serialized string for storage.
- Parameters
indent – Number of spaces for each indentation.
- classmethod from_dict(graph_dict: Union[Dict[str, List[str]], Dict[str, Set[str]], OrderedDict[str, Set[str]]], context: runway.context.CfnginContext) runway.cfngin.plan.Graph[source]
Create a Graph from a graph dict.
- Parameters
graph_dict – The dictionary used to create the graph.
context – Required to init stacks.
- classmethod from_steps(steps: List[runway.cfngin.plan.Step]) runway.cfngin.plan.Graph[source]
Create a Graph from Steps.
- Parameters
steps – Steps used to create the graph.
- __new__(**kwargs)
- class runway.cfngin.plan.Plan[source]
Bases:
objectA convenience class for working on a Graph.
- context
Context object.
- Type
Optional[CfnginContext]
- __init__(description: str, graph: Graph, context: Optional[CfnginContext] = None, reverse: bool = False, require_unlocked: bool = True) None[source]
Initialize class.
- Parameters
description – Description of what the plan is going to do.
graph – Local graph used for the plan.
context – Context object.
reverse – Transpose the graph for walking in reverse.
require_unlocked – Require the persistent graph to be unlocked before executing steps.
- __new__(**kwargs)
- outline(level: int = 20, message: str = '')[source]
Print an outline of the actions the plan is going to take.
The outline will represent the rough ordering of the steps that will be taken.
- Parameters
level – a valid log level that should be used to log the outline
message – a message that will be logged to the user after the outline has been logged.
- dump(*, directory: str, context: CfnginContext, provider: Optional[Provider] = None) Any[source]
Output the rendered blueprint for all stacks in the plan.
- Parameters
directory – Directory where files will be created.
context – Current CFNgin context.
provider – Provider to use when resolving the blueprints.
- execute(*args: Any, **kwargs: Any)[source]
Walk each step in the underlying graph.
- Raises
PersistentGraphLocked – Raised if the persistent graph is locked prior to execution and this session did not lock it.
PlanFailed – Raised if any of the steps fail.
- walk(walker: Callable[[...], Any]) Any[source]
Walk each step in the underlying graph, in topological order.
- Parameters
walker – a walker function to be passed to
runway.cfngin.dag.DAGto walk the graph.
- property steps: List[runway.cfngin.plan.Step]
Return a list of all steps in the plan.
CFNgin session caching.
- runway.cfngin.session_cache.get_session(region: Optional[str] = None, profile: Optional[str] = None, access_key: Optional[str] = None, secret_key: Optional[str] = None, session_token: Optional[str] = None) boto3.session.Session[source]
Create a thread-safe boto3 session.
- Parameters
region – The region for the session.
profile – The profile for the session.
access_key – AWS Access Key ID.
secret_key – AWS secret Access Key.
session_token – AWS session token.
- Returns
A thread-safe boto3 session.
CFNgin stack.
- class runway.cfngin.stack.Stack[source]
Bases:
objectRepresents gathered information about a stack to be built/updated.
- definition
The stack definition from the config.
- in_progress_behavior
The behavior for when a stack is in
CREATE_IN_PROGRESSorUPDATE_IN_PROGRESS.- Type
Optional[Literal[‘wait’]]
- mappings
Cloudformation mappings passed to the blueprint.
- __init__(definition: CfnginStackDefinitionModel, context: CfnginContext, *, variables: Optional[Dict[str, Any]] = None, mappings: Dict[str, Dict[str, Dict[str, Any]]] = None, locked: bool = False, force: bool = False, enabled: bool = True, protected: bool = False)[source]
Instantiate class.
- Parameters
definition – A stack definition.
context – Current context for deploying the stack.
variables – Variables for the stack.
mappings – Cloudformation mappings passed to the blueprint.
locked – Whether or not the stack is locked.
force – Whether to force updates on this stack.
enabled – Whether this stack is enabled
protected – Whether this stack is protected.
- __new__(**kwargs)
- property tags: Dict[str, Any]
Return the tags that should be set on this stack.
Includes both the global tags, as well as any stack specific tags or overrides.
- property parameter_values: Dict[str, Any]
Return all CloudFormation Parameters for the stack.
CloudFormation Parameters can be specified via Blueprint Variables with a
runway.cfngin.blueprints.variables.types.CFNTypetype.- Returns
Dictionary of
<parameter name>: <parameter value>.
- property all_parameter_definitions: Dict[str, Any]
Return all parameters in the blueprint/template.
- property required_parameter_definitions: Dict[str, Any]
Return all CloudFormation Parameters without a default value.
- resolve(context: CfnginContext, provider: Optional[Provider] = None) None[source]
Resolve the Stack variables.
This resolves the Stack variables and then prepares the Blueprint for rendering by passing the resolved variables to the Blueprint.
- Parameters
context – CFNgin context.
provider – Subclass of the base provider.
CFNgin statuses.
- class runway.cfngin.status.Status[source]
Bases:
objectCFNgin status base class.
- __init__(name: str, code: int, reason: Optional[str] = None) None[source]
Instantiate class.
- Parameters
name – Name of the status.
code – Status code.
reason – Reason for the status.
- __new__(**kwargs)
- class runway.cfngin.status.CompleteStatus[source]
Bases:
runway.cfngin.status.StatusStatus name of ‘complete’ with code of ‘2’.
- __init__(reason: Optional[str] = None) None[source]
Instantiate class.
- Parameters
reason – Reason for the status.
- __new__(**kwargs)
- class runway.cfngin.status.FailedStatus[source]
Bases:
runway.cfngin.status.StatusStatus name of ‘failed’ with code of ‘4’.
- __init__(reason: Optional[str] = None) None[source]
Instantiate class.
- Parameters
reason – Reason for the status.
- __new__(**kwargs)
- class runway.cfngin.status.PendingStatus[source]
Bases:
runway.cfngin.status.StatusStatus name of ‘pending’ with code of ‘0’.
- __init__(reason: Optional[str] = None) None[source]
Instantiate class.
- Parameters
reason – Reason for the status.
- __new__(**kwargs)
- class runway.cfngin.status.SkippedStatus[source]
Bases:
runway.cfngin.status.StatusStatus name of ‘skipped’ with code of ‘3’.
- __init__(reason: Optional[str] = None) None[source]
Instantiate class.
- Parameters
reason – Reason for the status.
- __new__(**kwargs)
- class runway.cfngin.status.SubmittedStatus[source]
Bases:
runway.cfngin.status.StatusStatus name of ‘submitted’ with code of ‘1’.
- __init__(reason: Optional[str] = None) None[source]
Instantiate class.
- Parameters
reason – Reason for the status.
- __new__(**kwargs)
- class runway.cfngin.status.DidNotChangeStatus[source]
Bases:
runway.cfngin.status.SkippedStatusSkipped status with a reason of ‘nochange’.
- __init__(reason: Optional[str] = None) None
Instantiate class.
- Parameters
reason – Reason for the status.
- __new__(**kwargs)
- class runway.cfngin.status.DoesNotExistInCloudFormation[source]
Bases:
runway.cfngin.status.SkippedStatusSkipped status with a reason of ‘does not exist in cloudformation’.
- __init__(reason: Optional[str] = None) None
Instantiate class.
- Parameters
reason – Reason for the status.
- __new__(**kwargs)
- class runway.cfngin.status.NotSubmittedStatus[source]
Bases:
runway.cfngin.status.SkippedStatusSkipped status with a reason of ‘disabled’.
- __init__(reason: Optional[str] = None) None
Instantiate class.
- Parameters
reason – Reason for the status.
- __new__(**kwargs)
Resources to tokenize userdata.
- runway.cfngin.tokenize_userdata.cf_tokenize(raw_userdata: str) List[str][source]
Parse UserData for Cloudformation helper functions.
http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/user-data.html
http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/intrinsic-function-reference.html
It breaks apart the given string at each recognized function (see
HELPERSglobal variable) and instantiates the helper function objects in place of those.- Parameters
raw_userdata – Unparsed userdata data string.
- Returns
A list of string parts that is useful when used with
troposphere.Join()andtroposphere.Base64()to produce userdata.
Example
CFNgin UI manipulation.
- runway.cfngin.ui.get_raw_input(message: str) str[source]
Just a wrapper for
input()for testing purposes.
- class runway.cfngin.ui.UI[source]
Bases:
ContextManager[UI]Used internally from terminal output in a multithreaded environment.
Ensures that two threads don’t write over each other while asking a user for input (e.g. in interactive mode).
- log(lvl: int, msg: Union[Exception, str], *args: Any, logger: Union[logging.Logger, logging.LoggerAdapter[Any]] = <RunwayLogger runway.cfngin.ui (WARNING)>, **kwargs: Any) None[source]
Log the message if the current thread owns the underlying lock.
- Parameters
lvl – Log level.
msg – String template or exception to use for the log record.
logger – Specific logger to log to.
- info(msg: str, *args: Any, logger: Union[logging.Logger, logging.LoggerAdapter[Any]] = <RunwayLogger runway.cfngin.ui (WARNING)>, **kwargs: Any) None[source]
Log the line if the current thread owns the underlying lock.
- Parameters
msg – String template or exception to use for the log record.
logger – Specific logger to log to.
- ask(message: str) str[source]
Collect input from a user in a multithreaded environment.
This wraps the built-in input function to ensure that only 1 thread is asking for input from the user at a give time. Any process that tries to log output to the terminal will be blocked while the user is being prompted.
- __enter__() runway.cfngin.ui.UI[source]
Enter the context manager.
- __exit__(exc_type: Optional[Type[BaseException]], exc_value: Optional[BaseException], traceback: Optional[TracebackType]) None[source]
Exit the context manager.
- __new__(**kwargs)
CFNgin utilities.
- runway.cfngin.utils.camel_to_snake(name: str) str[source]
Convert CamelCase to snake_case.
- Parameters
name (str) – The name to convert from CamelCase to snake_case.
- Returns
Converted string.
- Return type
- runway.cfngin.utils.convert_class_name(kls: type) str[source]
Get a string that represents a given class.
- Parameters
kls – The class being analyzed for its name.
- Returns
The name of the given kls.
- runway.cfngin.utils.parse_zone_id(full_zone_id: str) str[source]
Parse the returned hosted zone id and returns only the ID itself.
- runway.cfngin.utils.get_hosted_zone_by_name(client: Route53Client, zone_name: str) Optional[str][source]
Get the zone id of an existing zone by name.
- Parameters
client – The connection used to interact with Route53’s API.
zone_name – The name of the DNS hosted zone to create.
- Returns
The Id of the Hosted Zone.
- runway.cfngin.utils.get_or_create_hosted_zone(client: Route53Client, zone_name: str) str[source]
Get the Id of an existing zone, or create it.
- Parameters
client – The connection used to interact with Route53’s API.
zone_name – The name of the DNS hosted zone to create.
- Returns
The Id of the Hosted Zone.
- class runway.cfngin.utils.SOARecordText[source]
Bases:
objectRepresents the actual body of an SOARecord.
- __new__(**kwargs)
- class runway.cfngin.utils.SOARecord[source]
Bases:
objectRepresents an SOA record.
- __new__(**kwargs)
- runway.cfngin.utils.get_soa_record(client: Route53Client, zone_id: str, zone_name: str) SOARecord[source]
Get the SOA record for zone_name from zone_id.
- Parameters
client – The connection used to interact with Route53’s API.
zone_id – The AWS Route53 zone id of the hosted zone to query.
zone_name – The name of the DNS hosted zone to create.
- Returns
An object representing the parsed SOA record returned from AWS Route53.
- runway.cfngin.utils.create_route53_zone(client: Route53Client, zone_name: str) str[source]
Create the given zone_name if it doesn’t already exists.
Also sets the SOA negative caching TTL to something short (300 seconds).
- Parameters
client – The connection used to interact with Route53’s API.
zone_name – The name of the DNS hosted zone to create.
- Returns
The zone id returned from AWS for the existing, or newly created zone.
- runway.cfngin.utils.yaml_to_ordered_dict(stream: str, loader: typing.Union[typing.Type[yaml.loader.Loader], typing.Type[yaml.loader.SafeLoader]] = <class 'yaml.loader.SafeLoader'>) OrderedDict[str, Any][source]
yaml.load alternative with preserved dictionary order.
- Parameters
stream – YAML string to load.
loader – PyYAML loader class. Defaults to safe load.
- runway.cfngin.utils.uppercase_first_letter(string_: str) str[source]
Return string with first character upper case.
- runway.cfngin.utils.cf_safe_name(name: str) str[source]
Convert a name to a safe string for a CloudFormation resource.
Given a string, returns a name that is safe for use as a CloudFormation Resource. (ie: Only alphanumeric characters)
- runway.cfngin.utils.read_value_from_path(value: str, *, root_path: Optional[pathlib.Path] = None) str[source]
Enable translators to read values from files.
The value can be referred to with the file:// prefix.
Example
conf_key: ${kms file://kms_value.txt}
- runway.cfngin.utils.get_client_region(client: Any) str[source]
Get the region from a boto3 client.
- Parameters
client – The client to get the region from.
- Returns
AWS region string.
- runway.cfngin.utils.get_s3_endpoint(client: Any) str[source]
Get the s3 endpoint for the given boto3 client.
- Parameters
client – The client to get the endpoint from.
- Returns
The AWS endpoint for the client.
- runway.cfngin.utils.s3_bucket_location_constraint(region: Optional[str]) Optional[str][source]
Return the appropriate LocationConstraint info for a new S3 bucket.
When creating a bucket in a region OTHER than us-east-1, you need to specify a LocationConstraint inside the CreateBucketConfiguration argument. This function helps you determine the right value given a given client.
- Parameters
region – The region where the bucket will be created in.
- Returns
The string to use with the given client for creating a bucket.
- runway.cfngin.utils.ensure_s3_bucket(s3_client: S3Client, bucket_name: str, bucket_region: Optional[str] = None, *, create: bool = True, persist_graph: bool = False) None[source]
Ensure an s3 bucket exists, if it does not then create it.
- Parameters
s3_client – An s3 client used to verify and create the bucket.
bucket_name – The bucket being checked/created.
bucket_region – The region to create the bucket in. If not provided, will be determined by s3_client’s region.
create – Whether to create the bucket if it does not exist.
persist_graph – Check bucket for recommended settings. If creating a new bucket, it will be created with recommended settings.
- runway.cfngin.utils.parse_cloudformation_template(template: str) Dict[str, Any][source]
Parse CFN template string.
Leverages the vendored aws-cli yamlhelper to handle JSON or YAML templates.
- Parameters
template – The template body.
- runway.cfngin.utils.is_within_directory(directory: Path | str, target: str) bool[source]
Check if file is in directory.
Determines if the provided path is within a specific directory or its subdirectories.
- Parameters
directory (Union[Path, str]) – Path of the directory we’re checking.
target (str) – Path of the file we’re checking for containment.
- Returns
True if the target is in the directory or subdirectories, False otherwise.
- Return type
- runway.cfngin.utils.safe_tar_extract(tar: tarfile.TarFile, path: Path | str = '.', members: list[tarfile.TarInfo] | None = None, *, numeric_owner: bool = False)[source]
Safely extract the contents of a tar file to a specified directory.
This code is modified from a PR provided to Runway project to address CVE-2007-4559.
- Parameters
tar (TarFile) – The tar file object that will be extracted.
path (Union[Path, str], optional) – The directory to extract the tar into.
members (List[TarInfo] | None, optional) – List of TarInfo objects to extract.
numeric_owner (bool, optional) – Enable usage of owner and group IDs when extracting.
- Raises
Exception – If any tar file tries to go outside the specified area.
- class runway.cfngin.utils.Extractor[source]
Bases:
objectBase class for extractors.
- __init__(archive: Optional[pathlib.Path] = None) None[source]
Instantiate class.
- Parameters
archive (str) – Archive path.
- set_archive(dir_name: pathlib.Path) None[source]
Update archive filename to match directory name & extension.
- Parameters
dir_name – Archive directory name
- __new__(**kwargs)
- class runway.cfngin.utils.TarExtractor[source]
Bases:
runway.cfngin.utils.ExtractorExtracts tar archives.
- extract(destination: pathlib.Path) None[source]
Extract the archive.
- __init__(archive: Optional[pathlib.Path] = None) None
Instantiate class.
- Parameters
archive (str) – Archive path.
- __new__(**kwargs)
- set_archive(dir_name: pathlib.Path) None
Update archive filename to match directory name & extension.
- Parameters
dir_name – Archive directory name
- class runway.cfngin.utils.TarGzipExtractor[source]
Bases:
runway.cfngin.utils.ExtractorExtracts compressed tar archives.
- extract(destination: pathlib.Path) None[source]
Extract the archive.
- __init__(archive: Optional[pathlib.Path] = None) None
Instantiate class.
- Parameters
archive (str) – Archive path.
- __new__(**kwargs)
- set_archive(dir_name: pathlib.Path) None
Update archive filename to match directory name & extension.
- Parameters
dir_name – Archive directory name
- class runway.cfngin.utils.ZipExtractor[source]
Bases:
runway.cfngin.utils.ExtractorExtracts zip archives.
- extract(destination: pathlib.Path) None[source]
Extract the archive.
- __init__(archive: Optional[pathlib.Path] = None) None
Instantiate class.
- Parameters
archive (str) – Archive path.
- __new__(**kwargs)
- set_archive(dir_name: pathlib.Path) None
Update archive filename to match directory name & extension.
- Parameters
dir_name – Archive directory name
- class runway.cfngin.utils.SourceProcessor[source]
Bases:
objectMakes remote python package sources available in current environment.
- __init__(sources: CfnginPackageSourcesDefinitionModel, cache_dir: Path) None[source]
Process a config’s defined package sources.
- Parameters
sources – Package sources from CFNgin config dictionary.
cache_dir – Path where remote sources will be cached.
- fetch_local_package(config: LocalCfnginPackageSourceDefinitionModel) None[source]
Make a local path available to current CFNgin config.
- Parameters
config – Package source config.
- fetch_s3_package(config: S3CfnginPackageSourceDefinitionModel) None[source]
Make a remote S3 archive available for local use.
- Parameters
config – Package source config.
- fetch_git_package(config: GitCfnginPackageSourceDefinitionModel) None[source]
Make a remote git repository available for local use.
- Parameters
config – Package source config.
- update_paths_and_config(config: Union[GitCfnginPackageSourceDefinitionModel, LocalCfnginPackageSourceDefinitionModel, S3CfnginPackageSourceDefinitionModel], pkg_dir_name: str, pkg_cache_dir: Optional[Path] = None) None[source]
Handle remote source defined sys.paths & configs.
- Parameters
config – Package source config.
pkg_dir_name – Directory name of the CFNgin archive.
pkg_cache_dir – Fully qualified path to CFNgin cache cache directory.
- static git_ls_remote(uri: str, ref: str) str[source]
Determine the latest commit id for a given ref.
- Parameters
uri – Git URI.
ref – Git ref.
- static determine_git_ls_remote_ref(config: GitCfnginPackageSourceDefinitionModel) str[source]
Determine the ref to be used with the “git ls-remote” command.
- Parameters
config – Git package source config.
- Returns
A branch reference or “HEAD”.
- determine_git_ref(config: GitCfnginPackageSourceDefinitionModel) str[source]
Determine the ref to be used for
git checkout.- Parameters
config – Git package source config.
- Returns
A commit id or tag name.
- static sanitize_uri_path(uri: str) str[source]
Take a URI and converts it to a directory safe path.
- Parameters
uri – URI to sanitize.
- Returns
Directory name for the supplied uri.
- sanitize_git_path(uri: str, ref: Optional[str] = None) str[source]
Take a git URI and ref and converts it to a directory safe path.
- Parameters
uri – Git URI. (e.g.
git@github.com:foo/bar.git)ref – Git ref to be appended to the path.
- Returns
Directory name for the supplied uri
- __new__(**kwargs)
CFNgin config.
- class runway.config.BaseConfig[source]
Bases:
objectBase class for configurations.
- __init__(data: BaseModel, *, path: Optional[Path] = None) None[source]
Instantiate class.
- Parameters
data – The data model of the config file.
path – Path to the config file.
- dump(*, by_alias: bool = False, exclude: Optional[Union[AbstractSet[Union[int, str]], Mapping[Union[int, str], Any]]] = None, exclude_defaults: bool = False, exclude_none: bool = False, exclude_unset: bool = True, include: Optional[Union[AbstractSet[Union[int, str]], Mapping[Union[int, str], Any]]] = None) str[source]
Dump model to a YAML string.
- Parameters
by_alias – Whether field aliases should be used as keys in the returned dictionary.
exclude – Fields to exclude from the returned dictionary.
exclude_defaults – Whether fields which are equal to their default values (whether set or otherwise) should be excluded from the returned dictionary.
exclude_none – Whether fields which are equal to None should be excluded from the returned dictionary.
exclude_unset – Whether fields which were not explicitly set when creating the model should be excluded from the returned dictionary.
include – Fields to include in the returned dictionary.
- classmethod find_config_file(path: pathlib.Path) Optional[pathlib.Path][source]
Find a config file in the provided path.
- Parameters
path – The path to search for a config file.
- __new__(**kwargs)
- class runway.config.CfnginConfig[source]
Bases:
runway.config.BaseConfigPython representation of a CFNgin config file.
This is used internally by CFNgin to parse and validate a YAML formatted CFNgin configuration file, but can also be used in scripts to generate a CFNgin config file before handing it off to CFNgin to deploy/destroy.
Example:
from runway.cfngin.config import dump, Config, Stack vpc = Stack({ "name": "vpc", "class_path": "blueprints.VPC"}) config = Config() config.namespace = "prod" config.stacks = [vpc] print dump(config)
- EXCLUDE_REGEX = 'runway(\\..*)?\\.(yml|yaml)'
Regex for file names to exclude when looking for config files.
- EXCLUDE_LIST = ['bitbucket-pipelines.yml', 'buildspec.yml', 'docker-compose.yml']
Explicit files names to ignore when looking for config files.
- __new__(**kwargs)
- dump(*, by_alias: bool = False, exclude: Optional[Union[AbstractSet[Union[int, str]], Mapping[Union[int, str], Any]]] = None, exclude_defaults: bool = False, exclude_none: bool = False, exclude_unset: bool = True, include: Optional[Union[AbstractSet[Union[int, str]], Mapping[Union[int, str], Any]]] = None) str
Dump model to a YAML string.
- Parameters
by_alias – Whether field aliases should be used as keys in the returned dictionary.
exclude – Fields to exclude from the returned dictionary.
exclude_defaults – Whether fields which are equal to their default values (whether set or otherwise) should be excluded from the returned dictionary.
exclude_none – Whether fields which are equal to None should be excluded from the returned dictionary.
exclude_unset – Whether fields which were not explicitly set when creating the model should be excluded from the returned dictionary.
include – Fields to include in the returned dictionary.
- __init__(data: runway.config.models.cfngin.CfnginConfigDefinitionModel, *, path: Optional[pathlib.Path] = None, work_dir: Optional[pathlib.Path] = None) None[source]
Instantiate class.
- Parameters
data – The data model of the config file.
path – Path to the config file.
work_dir – Working directory.
- cfngin_bucket: Optional[str]
Bucket to use for CFNgin resources. (e.g. CloudFormation templates). May be an empty string.
- cfngin_bucket_region: Optional[str]
Explicit region to use for
CfnginConfig.cfngin_bucket
- cfngin_cache_dir: Path
Local directory to use for caching.
- namespace_delimiter: str
Character used to separate
CfnginConfig.namespaceand anything it prepends.
- package_sources: CfnginPackageSourcesDefinitionModel
Remote source locations.
- post_deploy: List[CfnginHookDefinitionModel]
Hooks to run after a deploy action.
- post_destroy: List[CfnginHookDefinitionModel]
Hooks to run after a destroy action.
- pre_deploy: List[CfnginHookDefinitionModel]
Hooks to run before a deploy action.
- pre_destroy: List[CfnginHookDefinitionModel]
Hooks to run before a destroy action.
- stacks: List[CfnginStackDefinitionModel]
Stacks to be processed.
- sys_path: Optional[Path]
Relative or absolute path to use as the work directory.
- classmethod find_config_file(path: Optional[pathlib.Path] = None, *, exclude: Optional[List[str]] = None) List[pathlib.Path][source]
Find a config file in the provided path.
- Parameters
path – The path to search for a config file.
exclude – List of file names to exclude. This list is appended to the global exclude list.
- Raises
ConfigNotFound – Could not find a config file in the provided path.
ValueError – More than one config file found in the provided path.
- classmethod parse_file(*, path: Optional[pathlib.Path] = None, file_path: Optional[pathlib.Path] = None, parameters: Optional[MutableMapping[str, Any]] = None, work_dir: Optional[pathlib.Path] = None, **kwargs: Any) runway.config.CfnginConfig[source]
Parse a YAML file to create a config object.
- Parameters
path – The path to search for a config file.
file_path – Exact path to a file to parse.
parameters – Values to use when resolving a raw config.
work_dir – Explicit working directory.
- Raises
ConfigNotFound – Provided config file was not found.
- classmethod parse_obj(obj: Any, *, path: Optional[pathlib.Path] = None, work_dir: Optional[pathlib.Path] = None) runway.config.CfnginConfig[source]
Parse a python object.
- Parameters
obj – A python object to parse as a CFNgin config.
path – The path to the config file that was parsed into the object.
work_dir – Working directory.
- classmethod parse_raw(data: str, *, parameters: Optional[MutableMapping[str, Any]] = None, path: Optional[pathlib.Path] = None, skip_package_sources: bool = False, work_dir: Optional[pathlib.Path] = None) runway.config.CfnginConfig[source]
Parse raw data.
- Parameters
data – The raw data to parse.
parameters – Values to use when resolving a raw config.
path – The path to search for a config file.
skip_package_sources – Skip processing package sources.
work_dir – Explicit working directory.
- classmethod process_package_sources(raw_data: str, *, parameters: Optional[MutableMapping[str, Any]] = None, work_dir: Optional[pathlib.Path] = None) str[source]
Process the package sources defined in a rendered config.
- Parameters
raw_data – Raw configuration data.
cache_dir – Directory to use when caching remote sources.
parameters – Values to use when resolving a raw config.
work_dir – Explicit working directory.
- static resolve_raw_data(raw_data: str, *, parameters: Optional[MutableMapping[str, Any]] = None) str[source]
Resolve raw data.
- Parameters
raw_data – Raw configuration data.
parameters – Values to use when resolving a raw config.
- Raises
MissingEnvironment – A value required by the config was not provided in parameters.
- class runway.config.RunwayConfig[source]
Bases:
runway.config.BaseConfigPython representation of a Runway config file.
- __new__(**kwargs)
- dump(*, by_alias: bool = False, exclude: Optional[Union[AbstractSet[Union[int, str]], Mapping[Union[int, str], Any]]] = None, exclude_defaults: bool = False, exclude_none: bool = False, exclude_unset: bool = True, include: Optional[Union[AbstractSet[Union[int, str]], Mapping[Union[int, str], Any]]] = None) str
Dump model to a YAML string.
- Parameters
by_alias – Whether field aliases should be used as keys in the returned dictionary.
exclude – Fields to exclude from the returned dictionary.
exclude_defaults – Whether fields which are equal to their default values (whether set or otherwise) should be excluded from the returned dictionary.
exclude_none – Whether fields which are equal to None should be excluded from the returned dictionary.
exclude_unset – Whether fields which were not explicitly set when creating the model should be excluded from the returned dictionary.
include – Fields to include in the returned dictionary.
- __init__(data: runway.config.models.runway.RunwayConfigDefinitionModel, *, path: Optional[pathlib.Path] = None) None[source]
Instantiate class.
- Parameters
data – The data model of the config file.
path – Path to the config file.
- classmethod find_config_file(path: pathlib.Path) pathlib.Path[source]
Find a config file in the provided path.
- Parameters
path – The path to search for a config file.
- Raises
ConfigNotFound – Could not find a config file in the provided path.
ValueError – More than one config file found in the provided path.
- classmethod parse_file(*, path: Optional[pathlib.Path] = None, file_path: Optional[pathlib.Path] = None, **kwargs: Any) runway.config.RunwayConfig[source]
Parse a YAML file to create a config object.
- Parameters
path – The path to search for a config file.
file_path – Exact path to a file to parse.
- Raises
ConfigNotFound – Provided config file was not found.
ValueError – path and file_path were both excluded.
- classmethod parse_obj(obj: Any, *, path: Optional[pathlib.Path] = None) runway.config.RunwayConfig[source]
Parse a python object into a config object.
- Parameters
obj – The object to be parsed.
path – Path to the file the object was parsed from.
Runway & CFNgin config components.
Runway config components.
- class runway.config.components.runway.CfnLintRunwayTestDefinition[source]
Bases:
runway.config.components.runway._test_def.RunwayTestDefinition[runway.config.models.runway._builtin_tests.CfnLintRunwayTestDefinitionModel]Runway cfn-lint test definition.
- __init__(data: runway.config.models.runway._builtin_tests.CfnLintRunwayTestDefinitionModel) None[source]
Instantiate class.
- classmethod parse_obj(obj: Any) runway.config.components.runway._test_def.CfnLintRunwayTestDefinition[source]
Parse a python object into this class.
- Parameters
obj – The object to parse.
- __getattr__(name: str)
Implement evaluation of self.name.
- Parameters
name – The value to look for.
- Raises
AttributeError – Object does not contain an attribute for the name provided.
UnresolvedVariable – The value being access is a variable and it has not been resolved yet.
- __getitem__(name: str)
Implement evaluation of self[name].
- Parameters
name – The value to look for.
- Raises
KeyError – Object does not contain a field of the name provided.
- static __new__(cls, data: runway.config.components.runway._test_def._DataModel) runway.config.components.runway._test_def.RunwayTestDefinition[runway.config.components.runway._test_def._DataModel]
Create a new instance of a class.
- Returns
Correct subclass of RunwayTestDefinition for the given data.
- __setattr__(name: str, value: Any) None
Implement evaluation of self.name = value.
When setting an attribute, the value is set on the underlying data model. The exception to this is if the name starts with an underscore.
- Parameters
name – The value to set.
value – The value to assigned to the field.
- Raises
AttributeError – The name being set is a property without a setter.
- __setitem__(name: str, value: Any) None
Implement evaluation of self[name] = value.
When setting an attribute, the value is set on the underlying data model. The exception to this is if the name starts with an underscore.
- Parameters
name – The value to set.
value – The value to assigned to the field.
- get(name: str, default: Optional[Any] = None) None
Get a value or return default if it is not found.
- Parameters
name – The value to look for.
default – Returned if no other value is found.
- resolve(context: RunwayContext, *, pre_process: bool = False, variables: Optional[RunwayVariablesDefinition] = None) None
Resolve variables.
- Parameters
context – Runway context object.
pre_process – Whether to only resolve pre-process fields.
variables – Object containing values to resolve the
varlookup.
- class runway.config.components.runway.RunwayDeploymentDefinition[source]
Bases:
runway.config.components.runway.base.ConfigComponentDefinitionRunway deployment definition.
- __init__(data: runway.config.models.runway.RunwayDeploymentDefinitionModel) None[source]
Instantiate class.
Return menu entry representation of this deployment.
- property modules: List[runway.config.components.runway._module_def.RunwayModuleDefinition]
List of Runway modules.
- set_modules(modules: List[Union[runway.config.components.runway._module_def.RunwayModuleDefinition, runway.config.models.runway.RunwayModuleDefinitionModel]]) None[source]
Set the value of modules.
- Parameters
modules – A list of modules.
- Raises
TypeError – The provided value does not match the required types.
- __getattr__(name: str)
Implement evaluation of self.name.
- Parameters
name – The value to look for.
- Raises
AttributeError – Object does not contain an attribute for the name provided.
UnresolvedVariable – The value being access is a variable and it has not been resolved yet.
- __getitem__(name: str)
Implement evaluation of self[name].
- Parameters
name – The value to look for.
- Raises
KeyError – Object does not contain a field of the name provided.
- __new__(**kwargs)
- __setattr__(name: str, value: Any) None
Implement evaluation of self.name = value.
When setting an attribute, the value is set on the underlying data model. The exception to this is if the name starts with an underscore.
- Parameters
name – The value to set.
value – The value to assigned to the field.
- Raises
AttributeError – The name being set is a property without a setter.
- __setitem__(name: str, value: Any) None
Implement evaluation of self[name] = value.
When setting an attribute, the value is set on the underlying data model. The exception to this is if the name starts with an underscore.
- Parameters
name – The value to set.
value – The value to assigned to the field.
- get(name: str, default: Optional[Any] = None) None
Get a value or return default if it is not found.
- Parameters
name – The value to look for.
default – Returned if no other value is found.
- resolve(context: RunwayContext, *, pre_process: bool = False, variables: Optional[RunwayVariablesDefinition] = None) None
Resolve variables.
- Parameters
context – Runway context object.
pre_process – Whether to only resolve pre-process fields.
variables – Object containing values to resolve the
varlookup.
- classmethod parse_obj(obj: List[Dict[str, Any]]) List[runway.config.components.runway._deployment_def.RunwayDeploymentDefinition][source]
- classmethod parse_obj(obj: Union[List[ConfigProperty], Set[ConfigProperty], Tuple[ConfigProperty, ...]]) List[runway.config.components.runway._deployment_def.RunwayDeploymentDefinition]
- classmethod parse_obj(obj: Union[Dict[str, Any], ConfigProperty]) runway.config.components.runway._deployment_def.RunwayDeploymentDefinition
Parse a python object into this class.
- Parameters
obj – The object to parse.
- class runway.config.components.runway.RunwayModuleDefinition[source]
Bases:
runway.config.components.runway.base.ConfigComponentDefinitionRunway module definition.
- __init__(data: runway.config.models.runway.RunwayModuleDefinitionModel) None[source]
Instantiate class.
- property child_modules: List[runway.config.components.runway._module_def.RunwayModuleDefinition]
List of child modules.
Return menu entry representation of this module.
- __getattr__(name: str)
Implement evaluation of self.name.
- Parameters
name – The value to look for.
- Raises
AttributeError – Object does not contain an attribute for the name provided.
UnresolvedVariable – The value being access is a variable and it has not been resolved yet.
- __getitem__(name: str)
Implement evaluation of self[name].
- Parameters
name – The value to look for.
- Raises
KeyError – Object does not contain a field of the name provided.
- __new__(**kwargs)
- __setattr__(name: str, value: Any) None
Implement evaluation of self.name = value.
When setting an attribute, the value is set on the underlying data model. The exception to this is if the name starts with an underscore.
- Parameters
name – The value to set.
value – The value to assigned to the field.
- Raises
AttributeError – The name being set is a property without a setter.
- __setitem__(name: str, value: Any) None
Implement evaluation of self[name] = value.
When setting an attribute, the value is set on the underlying data model. The exception to this is if the name starts with an underscore.
- Parameters
name – The value to set.
value – The value to assigned to the field.
- get(name: str, default: Optional[Any] = None) None
Get a value or return default if it is not found.
- Parameters
name – The value to look for.
default – Returned if no other value is found.
- classmethod parse_obj(obj: Any) runway.config.components.runway._module_def.RunwayModuleDefinition[source]
Parse a python object into this class.
- Parameters
obj – The object to parse.
- resolve(context: RunwayContext, *, pre_process: bool = False, variables: Optional[RunwayVariablesDefinition] = None) None
Resolve variables.
- Parameters
context – Runway context object.
pre_process – Whether to only resolve pre-process fields.
variables – Object containing values to resolve the
varlookup.
- class runway.config.components.runway.RunwayTestDefinition[source]
Bases:
Generic[runway.config.components.runway._test_def._DataModel],runway.config.components.runway.base.ConfigComponentDefinitionRunway test definition.
- __init__(data: runway.config.components.runway._test_def._DataModel) None[source]
Instantiate class.
- static __new__(cls, data: runway.config.components.runway._test_def._DataModel) runway.config.components.runway._test_def.RunwayTestDefinition[runway.config.components.runway._test_def._DataModel][source]
Create a new instance of a class.
- Returns
Correct subclass of RunwayTestDefinition for the given data.
- classmethod parse_obj(obj: Any) runway.config.components.runway._test_def.RunwayTestDefinition[runway.config.components.runway._test_def._DataModel][source]
Parse a python object into this class.
- Parameters
obj – The object to parse.
- __getattr__(name: str)
Implement evaluation of self.name.
- Parameters
name – The value to look for.
- Raises
AttributeError – Object does not contain an attribute for the name provided.
UnresolvedVariable – The value being access is a variable and it has not been resolved yet.
- __getitem__(name: str)
Implement evaluation of self[name].
- Parameters
name – The value to look for.
- Raises
KeyError – Object does not contain a field of the name provided.
- __setattr__(name: str, value: Any) None
Implement evaluation of self.name = value.
When setting an attribute, the value is set on the underlying data model. The exception to this is if the name starts with an underscore.
- Parameters
name – The value to set.
value – The value to assigned to the field.
- Raises
AttributeError – The name being set is a property without a setter.
- __setitem__(name: str, value: Any) None
Implement evaluation of self[name] = value.
When setting an attribute, the value is set on the underlying data model. The exception to this is if the name starts with an underscore.
- Parameters
name – The value to set.
value – The value to assigned to the field.
- get(name: str, default: Optional[Any] = None) None
Get a value or return default if it is not found.
- Parameters
name – The value to look for.
default – Returned if no other value is found.
- resolve(context: RunwayContext, *, pre_process: bool = False, variables: Optional[RunwayVariablesDefinition] = None) None
Resolve variables.
- Parameters
context – Runway context object.
pre_process – Whether to only resolve pre-process fields.
variables – Object containing values to resolve the
varlookup.
- class runway.config.components.runway.RunwayVariablesDefinition[source]
Bases:
runway.utils.MutableMapRunway variables definition.
- __init__(data: runway.config.models.runway.RunwayVariablesDefinitionModel) None[source]
Instantiate class.
- classmethod parse_obj(obj: Any) runway.config.components.runway._variables_def.RunwayVariablesDefinition[source]
Parse a python object into this class.
- Parameters
obj – The object to parse.
- __delitem__(key: str) None
Implement deletion of self[key].
- Parameters
key – Attribute name to remove from the object.
Example
- __getitem__(key: str) Any
Implement evaluation of self[key].
- Parameters
key – Attribute name to return the value for.
- Returns
The value associated with the provided key/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
Example
- __new__(**kwargs)
- __setitem__(key: str, value: Any) None
Implement assignment to self[key].
- Parameters
key – Attribute name to associate with a value.
value – Value of a key/attribute.
Example
- clear() None. Remove all items from D.
- find(query: str, default: Optional[Any] = None, ignore_cache: bool = False) Any
Find a value in the map.
Previously found queries are cached to increase search speed. The cached value should only be used if values are not expected to change.
- Parameters
query – A period delimited string that is split to search for nested values
default – The value to return if the query was unsuccessful.
ignore_cache – Ignore cached value.
- get(key: str, default: Optional[Any] = None) Any
Implement evaluation of self.get.
- Parameters
key – Attribute name to return the value for.
default – Value to return if attribute is not found.
- items() a set-like object providing a view on D's items
- keys() a set-like object providing a view on D's keys
- pop(k[, d]) v, remove specified key and return the corresponding value.
If key is not found, d is returned if given, otherwise KeyError is raised.
- popitem() (k, v), remove and return some (key, value) pair
as a 2-tuple; but raise KeyError if D is empty.
- setdefault(k[, d]) D.get(k,d), also set D[k]=d if k not in D
- update([E, ]**F) None. Update D from mapping/iterable E and F.
If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v
- values() an object providing a view on D's values
- class runway.config.components.runway.ScriptRunwayTestDefinition[source]
Bases:
runway.config.components.runway._test_def.RunwayTestDefinition[runway.config.models.runway._builtin_tests.ScriptRunwayTestDefinitionModel]Runway script test definition.
- __init__(data: runway.config.models.runway._builtin_tests.ScriptRunwayTestDefinitionModel) None[source]
Instantiate class.
- classmethod parse_obj(obj: Any) runway.config.components.runway._test_def.ScriptRunwayTestDefinition[source]
Parse a python object into this class.
- Parameters
obj – The object to parse.
- __getattr__(name: str)
Implement evaluation of self.name.
- Parameters
name – The value to look for.
- Raises
AttributeError – Object does not contain an attribute for the name provided.
UnresolvedVariable – The value being access is a variable and it has not been resolved yet.
- __getitem__(name: str)
Implement evaluation of self[name].
- Parameters
name – The value to look for.
- Raises
KeyError – Object does not contain a field of the name provided.
- static __new__(cls, data: runway.config.components.runway._test_def._DataModel) runway.config.components.runway._test_def.RunwayTestDefinition[runway.config.components.runway._test_def._DataModel]
Create a new instance of a class.
- Returns
Correct subclass of RunwayTestDefinition for the given data.
- __setattr__(name: str, value: Any) None
Implement evaluation of self.name = value.
When setting an attribute, the value is set on the underlying data model. The exception to this is if the name starts with an underscore.
- Parameters
name – The value to set.
value – The value to assigned to the field.
- Raises
AttributeError – The name being set is a property without a setter.
- __setitem__(name: str, value: Any) None
Implement evaluation of self[name] = value.
When setting an attribute, the value is set on the underlying data model. The exception to this is if the name starts with an underscore.
- Parameters
name – The value to set.
value – The value to assigned to the field.
- get(name: str, default: Optional[Any] = None) None
Get a value or return default if it is not found.
- Parameters
name – The value to look for.
default – Returned if no other value is found.
- resolve(context: RunwayContext, *, pre_process: bool = False, variables: Optional[RunwayVariablesDefinition] = None) None
Resolve variables.
- Parameters
context – Runway context object.
pre_process – Whether to only resolve pre-process fields.
variables – Object containing values to resolve the
varlookup.
- class runway.config.components.runway.YamlLintRunwayTestDefinition[source]
Bases:
runway.config.components.runway._test_def.RunwayTestDefinition[runway.config.models.runway._builtin_tests.YamlLintRunwayTestDefinitionModel]Runway yamllint test definition.
- __init__(data: runway.config.models.runway._builtin_tests.YamlLintRunwayTestDefinitionModel) None[source]
Instantiate class.
- classmethod parse_obj(obj: Any) runway.config.components.runway._test_def.YamlLintRunwayTestDefinition[source]
Parse a python object into this class.
- Parameters
obj – The object to parse.
- __getattr__(name: str)
Implement evaluation of self.name.
- Parameters
name – The value to look for.
- Raises
AttributeError – Object does not contain an attribute for the name provided.
UnresolvedVariable – The value being access is a variable and it has not been resolved yet.
- __getitem__(name: str)
Implement evaluation of self[name].
- Parameters
name – The value to look for.
- Raises
KeyError – Object does not contain a field of the name provided.
- static __new__(cls, data: runway.config.components.runway._test_def._DataModel) runway.config.components.runway._test_def.RunwayTestDefinition[runway.config.components.runway._test_def._DataModel]
Create a new instance of a class.
- Returns
Correct subclass of RunwayTestDefinition for the given data.
- __setattr__(name: str, value: Any) None
Implement evaluation of self.name = value.
When setting an attribute, the value is set on the underlying data model. The exception to this is if the name starts with an underscore.
- Parameters
name – The value to set.
value – The value to assigned to the field.
- Raises
AttributeError – The name being set is a property without a setter.
- __setitem__(name: str, value: Any) None
Implement evaluation of self[name] = value.
When setting an attribute, the value is set on the underlying data model. The exception to this is if the name starts with an underscore.
- Parameters
name – The value to set.
value – The value to assigned to the field.
- get(name: str, default: Optional[Any] = None) None
Get a value or return default if it is not found.
- Parameters
name – The value to look for.
default – Returned if no other value is found.
- resolve(context: RunwayContext, *, pre_process: bool = False, variables: Optional[RunwayVariablesDefinition] = None) None
Resolve variables.
- Parameters
context – Runway context object.
pre_process – Whether to only resolve pre-process fields.
variables – Object containing values to resolve the
varlookup.
Runway config base definition.
- class runway.config.components.runway.base.ConfigComponentDefinition[source]
Bases:
abc.ABCBase class for Runway config components.
- __init__(data: ConfigProperty) None[source]
Instantiate class.
- get(name: str, default: Optional[Any] = None) None[source]
Get a value or return default if it is not found.
- Parameters
name – The value to look for.
default – Returned if no other value is found.
- resolve(context: RunwayContext, *, pre_process: bool = False, variables: Optional[RunwayVariablesDefinition] = None) None[source]
Resolve variables.
- Parameters
context – Runway context object.
pre_process – Whether to only resolve pre-process fields.
variables – Object containing values to resolve the
varlookup.
- abstract classmethod parse_obj(obj: Any) runway.config.components.runway.base.ConfigComponentDefinition[source]
Parse a python object into this class.
- Parameters
obj – The object to parse.
- __getattr__(name: str)[source]
Implement evaluation of self.name.
- Parameters
name – The value to look for.
- Raises
AttributeError – Object does not contain an attribute for the name provided.
UnresolvedVariable – The value being access is a variable and it has not been resolved yet.
- __getitem__(name: str)[source]
Implement evaluation of self[name].
- Parameters
name – The value to look for.
- Raises
KeyError – Object does not contain a field of the name provided.
- __new__(**kwargs)
- __setattr__(name: str, value: Any) None[source]
Implement evaluation of self.name = value.
When setting an attribute, the value is set on the underlying data model. The exception to this is if the name starts with an underscore.
- Parameters
name – The value to set.
value – The value to assigned to the field.
- Raises
AttributeError – The name being set is a property without a setter.
- __setitem__(name: str, value: Any) None[source]
Implement evaluation of self[name] = value.
When setting an attribute, the value is set on the underlying data model. The exception to this is if the name starts with an underscore.
- Parameters
name – The value to set.
value – The value to assigned to the field.
Runway & CFNgin config models.
CFNgin config models.
- class runway.config.models.cfngin.CfnginConfigDefinitionModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for a CFNgin config definition.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- classmethod parse_file(path: Union[str, Path], *, content_type: Optional[str] = None, encoding: str = 'utf8', proto: Optional[Protocol] = None, allow_pickle: bool = False) Model[source]
Parse a file.
- classmethod parse_raw(b: Union[bytes, str], *, content_type: Optional[str] = None, encoding: str = 'utf8', proto: Optional[Protocol] = None, allow_pickle: bool = False) Model[source]
Parse raw data.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.cfngin.CfnginHookDefinitionModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for a CFNgin hook definition.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.cfngin.CfnginPackageSourcesDefinitionModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for a CFNgin package sources definition.
- git
Package source located in a git repo.
- local
Package source located on a local disk.
- s3
Package source located in AWS S3.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.cfngin.CfnginStackDefinitionModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for a CFNgin stack definition.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration options.
- static schema_extra(schema: Dict[str, Any]) None[source]
Process the schema after it has been generated.
Schema is modified in place. Return value is ignored.
https://pydantic-docs.helpmanual.io/usage/schema/#schema-customization
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.cfngin.GitCfnginPackageSourceDefinitionModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for a git package source definition.
Package source located in a git repository.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.cfngin.LocalCfnginPackageSourceDefinitionModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for a CFNgin local package source definition.
Package source located on a local disk.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.cfngin.S3CfnginPackageSourceDefinitionModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for a CFNgin S3 package source definition.
Package source located in AWS S3.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
Runway config models.
- class runway.config.models.runway.CfnLintRunwayTestArgs[source]
Bases:
runway.config.models.base.ConfigPropertyModel for the args of a cfn-lint test.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.runway.CfnLintRunwayTestDefinitionModel[source]
Bases:
runway.config.models.runway._builtin_tests.RunwayTestDefinitionModelModel for a cfn-lint test definition.
- class Config[source]
Bases:
runway.config.models.runway._builtin_tests.RunwayTestDefinitionModel.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- static __new__(cls, **kwargs: Any) runway.config.models.runway._builtin_tests.RunwayTestDefinitionModel
Create a new instance of a class.
- Returns
Correct subclass of RunwayTestDefinition for the given data.
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.runway.RunwayAssumeRoleDefinitionModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for a Runway assume role definition.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.runway.RunwayConfigDefinitionModel[source]
Bases:
runway.config.models.base.ConfigPropertyRunway configuration definition model.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- classmethod parse_file(path: Union[str, Path], *, content_type: Optional[str] = None, encoding: str = 'utf8', proto: Optional[Protocol] = None, allow_pickle: bool = False) Model[source]
Parse a file.
- classmethod parse_raw(b: Union[bytes, str], *, content_type: Optional[str] = None, encoding: str = 'utf8', proto: Optional[Protocol] = None, allow_pickle: bool = False) Model[source]
Parse raw data.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.runway.RunwayDeploymentDefinitionModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for a Runway deployment definition.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- static schema_extra(schema: Dict[str, Any]) None[source]
Process the schema after it has been generated.
Schema is modified in place. Return value is ignored.
https://pydantic-docs.helpmanual.io/usage/schema/#schema-customization
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.runway.RunwayDeploymentRegionDefinitionModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for a Runway deployment region definition.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.runway.RunwayFutureDefinitionModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for the Runway future definition.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.runway.RunwayModuleDefinitionModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for a Runway module definition.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.runway.RunwayTestDefinitionModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for a Runway test definition.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- static __new__(cls, **kwargs: Any) runway.config.models.runway._builtin_tests.RunwayTestDefinitionModel[source]
Create a new instance of a class.
- Returns
Correct subclass of RunwayTestDefinition for the given data.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.runway.RunwayVariablesDefinitionModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for a Runway variable definition.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.runway.RunwayVersionField[source]
Bases:
packaging.specifiers.SpecifierSetExtends packaging.specifiers.SpecifierSet for use with pydantic.
- classmethod __get_validators__() Generator[Callable[[...], Any], None, None][source]
Yield one of more validators with will be called to validate the input.
Each validator will receive, as input, the value returned from the previous validator.
- classmethod __modify_schema__(field_schema: Dict[str, Any]) None[source]
Mutate the field schema in place.
This is only called when output JSON schema from a model.
- __and__(other: Union[packaging.specifiers.SpecifierSet, str]) packaging.specifiers.SpecifierSet
Return a SpecifierSet which is a combination of the two sets.
- Parameters
other – The other object to combine with.
>>> SpecifierSet(">=1.0.0,!=1.0.1") & '<=2.0.0,!=2.0.1' <SpecifierSet('!=1.0.1,!=2.0.1,<=2.0.0,>=1.0.0')> >>> SpecifierSet(">=1.0.0,!=1.0.1") & SpecifierSet('<=2.0.0,!=2.0.1') <SpecifierSet('!=1.0.1,!=2.0.1,<=2.0.0,>=1.0.0')>
- __contains__(item: Union[packaging.version.Version, str]) bool
Return whether or not the item is contained in this specifier.
- Parameters
item – The item to check for.
This is used for the
inoperator and behaves the same ascontains()with noprereleasesargument passed.>>> "1.2.3" in SpecifierSet(">=1.0.0,!=1.0.1") True >>> Version("1.2.3") in SpecifierSet(">=1.0.0,!=1.0.1") True >>> "1.0.1" in SpecifierSet(">=1.0.0,!=1.0.1") False >>> "1.3.0a1" in SpecifierSet(">=1.0.0,!=1.0.1") False >>> "1.3.0a1" in SpecifierSet(">=1.0.0,!=1.0.1", prereleases=True) True
- __eq__(other: object) bool
Whether or not the two SpecifierSet-like objects are equal.
- Parameters
other – The other object to check against.
The value of
prereleasesis ignored.>>> SpecifierSet(">=1.0.0,!=1.0.1") == SpecifierSet(">=1.0.0,!=1.0.1") True >>> (SpecifierSet(">=1.0.0,!=1.0.1", prereleases=False) == ... SpecifierSet(">=1.0.0,!=1.0.1", prereleases=True)) True >>> SpecifierSet(">=1.0.0,!=1.0.1") == ">=1.0.0,!=1.0.1" True >>> SpecifierSet(">=1.0.0,!=1.0.1") == SpecifierSet(">=1.0.0") False >>> SpecifierSet(">=1.0.0,!=1.0.1") == SpecifierSet(">=1.0.0,!=1.0.2") False
- __init__(specifiers: str = '', prereleases: Optional[bool] = None) None
Initialize a SpecifierSet instance.
- Parameters
specifiers – The string representation of a specifier or a comma-separated list of specifiers which will be parsed and normalized before use.
prereleases – This tells the SpecifierSet if it should accept prerelease versions if applicable or not. The default of
Nonewill autodetect it from the given specifiers.
- Raises
InvalidSpecifier – If the given
specifiersare not parseable than this exception will be raised.
- __iter__() Iterator[packaging.specifiers.Specifier]
Returns an iterator over all the underlying
Specifierinstances in this specifier set.>>> sorted(SpecifierSet(">=1.0.0,!=1.0.1"), key=str) [<Specifier('!=1.0.1')>, <Specifier('>=1.0.0')>]
- __new__(**kwargs)
- __repr__() str
A representation of the specifier set that shows all internal state.
Note that the ordering of the individual specifiers within the set may not match the input string.
>>> SpecifierSet('>=1.0.0,!=2.0.0') <SpecifierSet('!=2.0.0,>=1.0.0')> >>> SpecifierSet('>=1.0.0,!=2.0.0', prereleases=False) <SpecifierSet('!=2.0.0,>=1.0.0', prereleases=False)> >>> SpecifierSet('>=1.0.0,!=2.0.0', prereleases=True) <SpecifierSet('!=2.0.0,>=1.0.0', prereleases=True)>
- __str__() str
A string representation of the specifier set that can be round-tripped.
Note that the ordering of the individual specifiers within the set may not match the input string.
>>> str(SpecifierSet(">=1.0.0,!=1.0.1")) '!=1.0.1,>=1.0.0' >>> str(SpecifierSet(">=1.0.0,!=1.0.1", prereleases=False)) '!=1.0.1,>=1.0.0'
- contains(item: Union[packaging.version.Version, str], prereleases: Optional[bool] = None, installed: Optional[bool] = None) bool
Return whether or not the item is contained in this SpecifierSet.
- Parameters
item – The item to check for, which can be a version string or a
Versioninstance.prereleases – Whether or not to match prereleases with this SpecifierSet. If set to
None(the default), it usesprereleasesto determine whether or not prereleases are allowed.
>>> SpecifierSet(">=1.0.0,!=1.0.1").contains("1.2.3") True >>> SpecifierSet(">=1.0.0,!=1.0.1").contains(Version("1.2.3")) True >>> SpecifierSet(">=1.0.0,!=1.0.1").contains("1.0.1") False >>> SpecifierSet(">=1.0.0,!=1.0.1").contains("1.3.0a1") False >>> SpecifierSet(">=1.0.0,!=1.0.1", prereleases=True).contains("1.3.0a1") True >>> SpecifierSet(">=1.0.0,!=1.0.1").contains("1.3.0a1", prereleases=True) True
- filter(iterable: Iterable[packaging.specifiers.UnparsedVersionVar], prereleases: Optional[bool] = None) Iterator[packaging.specifiers.UnparsedVersionVar]
Filter items in the given iterable, that match the specifiers in this set.
- Parameters
iterable – An iterable that can contain version strings and
Versioninstances. The items in the iterable will be filtered according to the specifier.prereleases – Whether or not to allow prereleases in the returned iterator. If set to
None(the default), it will be intelligently decide whether to allow prereleases or not (based on theprereleasesattribute, and whether the only versions matching are prereleases).
This method is smarter than just
filter(SpecifierSet(...).contains, [...])because it implements the rule from PEP 440 that a prerelease item SHOULD be accepted if no other versions match the given specifier.>>> list(SpecifierSet(">=1.2.3").filter(["1.2", "1.3", "1.5a1"])) ['1.3'] >>> list(SpecifierSet(">=1.2.3").filter(["1.2", "1.3", Version("1.4")])) ['1.3', <Version('1.4')>] >>> list(SpecifierSet(">=1.2.3").filter(["1.2", "1.5a1"])) [] >>> list(SpecifierSet(">=1.2.3").filter(["1.3", "1.5a1"], prereleases=True)) ['1.3', '1.5a1'] >>> list(SpecifierSet(">=1.2.3", prereleases=True).filter(["1.3", "1.5a1"])) ['1.3', '1.5a1']
An “empty” SpecifierSet will filter items based on the presence of prerelease versions in the set.
>>> list(SpecifierSet("").filter(["1.3", "1.5a1"])) ['1.3'] >>> list(SpecifierSet("").filter(["1.5a1"])) ['1.5a1'] >>> list(SpecifierSet("", prereleases=True).filter(["1.3", "1.5a1"])) ['1.3', '1.5a1'] >>> list(SpecifierSet("").filter(["1.3", "1.5a1"], prereleases=True)) ['1.3', '1.5a1']
- class runway.config.models.runway.ScriptRunwayTestArgs[source]
Bases:
runway.config.models.base.ConfigPropertyModel for the args of a script test.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.runway.ScriptRunwayTestDefinitionModel[source]
Bases:
runway.config.models.runway._builtin_tests.RunwayTestDefinitionModelModel for a script test definition.
- class Config[source]
Bases:
runway.config.models.runway._builtin_tests.RunwayTestDefinitionModel.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- static __new__(cls, **kwargs: Any) runway.config.models.runway._builtin_tests.RunwayTestDefinitionModel
Create a new instance of a class.
- Returns
Correct subclass of RunwayTestDefinition for the given data.
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.runway.YamlLintRunwayTestDefinitionModel[source]
Bases:
runway.config.models.runway._builtin_tests.RunwayTestDefinitionModelModel for a yamllint test definition.
- class Config[source]
Bases:
runway.config.models.runway._builtin_tests.RunwayTestDefinitionModel.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- static __new__(cls, **kwargs: Any) runway.config.models.runway._builtin_tests.RunwayTestDefinitionModel
Create a new instance of a class.
- Returns
Correct subclass of RunwayTestDefinition for the given data.
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
Runway module options.
Runway AWS Cloud Development Kit Module options.
- class runway.config.models.runway.options.cdk.RunwayCdkModuleOptionsDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway AWS Cloud Development Kit Module options.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
Runway Kubernetes Module options.
- class runway.config.models.runway.options.k8s.RunwayK8sModuleOptionsDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway Kubernetes Module options.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
Runway Serverless Framework Module options.
- class runway.config.models.runway.options.serverless.RunwayServerlessPromotezipOptionDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway Serverless module promotezip option.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.runway.options.serverless.RunwayServerlessModuleOptionsDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway Serverless Framework Module options.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
Runway Terraform Module options.
- class runway.config.models.runway.options.terraform.RunwayTerraformArgsDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway Terraform Module args option.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.runway.options.terraform.RunwayTerraformBackendConfigDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway Terraform Module terraform_backend_config option.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.config.models.runway.options.terraform.RunwayTerraformModuleOptionsDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway Terraform Module options.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
Base models & other objects.
- class runway.config.models.base.ConfigProperty[source]
Bases:
runway.utils.BaseModelBase class for Runway configuration properties.
- class Config[source]
Bases:
pydantic.config.BaseConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
Runway & CFNgin config model utilities.
- runway.config.models.utils.convert_null_values(v: Any) Any[source]
Convert a “null” string into type(None).
- runway.config.models.utils.resolve_path_field(v: Optional[pathlib.Path]) Optional[pathlib.Path][source]
Resolve sys_path.
Context objects.
- class runway.context.CfnginContext[source]
Bases:
runway.context._base.BaseContextCFNgin context object.
- bucket_region
Region where the S3 Bucket is located. The S3 Bucket being the Bucket configured for staging CloudFormation Templates.
- Type
- config
CFNgin configuration file that has been resolved & parsed into a python object.
- Type
- config_path
Path to the configuration file that has been resolved, parsed and made accessible via this object.
- Type
Path
- env
Deploy environment object containing information about the current deploy environment.
- Type
- hook_data
Values returned by hooks that are stored based on the
data_keydefined for the hook. Returned values are only stored if adata_keywas provided AND the return value is a dict orpydantic.BaseModel.- Type
Dict[str, Any]
- logger
Custom logger to use when logging messages.
- Type
Union[PrefixAdaptor, RunwayLogger]
- stack_names
List of Stack names to operate on. If value is falsy, all Stacks defined in the config will be operated on.
- Type
List[str]
- __init__(*, config: typing.Optional[runway.config.CfnginConfig] = None, config_path: typing.Optional[pathlib.Path] = None, deploy_environment: typing.Optional[runway.core.components._deploy_environment.DeployEnvironment] = None, force_stacks: typing.Optional[typing.List[str]] = None, logger: typing.Union[runway._logging.PrefixAdaptor, runway._logging.RunwayLogger] = <RunwayLogger runway.context._cfngin (WARNING)>, parameters: typing.Optional[typing.MutableMapping[str, typing.Any]] = None, stack_names: typing.Optional[typing.List[str]] = None, work_dir: typing.Optional[pathlib.Path] = None, **_: typing.Any) None[source]
Instantiate class.
- Parameters
config – The CFNgin configuration being operated on.
config_path – Path to the config file that was provided.
deploy_environment – The current deploy environment.
force_stacks – A list of stacks to force work on. Used to work on locked stacks.
logger – Custom logger.
parameters – Parameters passed from Runway or read from a file.
stack_names – A list of stack_names to operate on. If not passed, all stacks defined in the config will be operated on.
work_dir – Working directory used by Runway.
- property persistent_graph_location: PersistentGraphLocation
Location of the persistent graph in s3.
- property persistent_graph_lock_code: Optional[str]
Code used to lock the persistent graph S3 object.
- property persistent_graph: Optional[runway.cfngin.plan.Graph]
Graph if a persistent graph is being used.
Will create an “empty” object in S3 if one is not found.
- property s3_bucket_verified: bool
Check CFNgin bucket exists and you have access.
If the CFNgin bucket does not exist, will try to create one.
- property s3_client: S3Client
AWS S3 client.
- property stacks_dict: Dict[str, runway.cfngin.stack.Stack]
Construct a dict of
{stack.fqn: Stack}for easy access to stacks.
- __new__(**kwargs)
- property boto3_credentials: runway.type_defs.Boto3CredentialsTypeDef
Return a dict of boto3 credentials.
- property current_aws_creds: EnvVarsAwsCredentialsTypeDef
AWS credentials from self.env_vars.
- get_session(*, aws_access_key_id: Optional[str] = None, aws_secret_access_key: Optional[str] = None, aws_session_token: Optional[str] = None, profile: Optional[str] = None, region: Optional[str] = None) boto3.session.Session
Create a thread-safe boto3 session.
If
profileis provided, it will take priority.If no credential arguments are passed, will attempt to find them in environment variables.
- Parameters
aws_access_key_id – AWS Access Key ID.
aws_secret_access_key – AWS secret Access Key.
aws_session_token – AWS session token.
profile – The profile for the session.
region – The region for the session.
- Returns
A thread-safe boto3 session.
- property is_interactive: bool
Whether the user should be prompted or not.
Determined by the existed of
CIin the environment.
- property is_noninteractive: bool
Whether the user should be prompted or not.
Determined by the existed of
CIin the environment. Inverse ofis_interactiveproperty.
- property stacks: List[runway.cfngin.stack.Stack]
Stacks for the current action.
- sys_info: SystemInfo
Information about the current system being used to run Runway.
- work_dir: Path
Working directory used by Runway. Should always be a directory named
.runway.
- copy() runway.context.CfnginContext[source]
Copy the contents of this object into a new instance.
- get_fqn(name: Optional[str] = None) str[source]
Return the fully qualified name of an object within this context.
If the name passed already appears to be a fully qualified name, it will be returned with no further processing.
- get_stack(name: str) Optional[runway.cfngin.stack.Stack][source]
Get a stack by name.
- Parameters
name – Name of a Stack as defined in the config.
- lock_persistent_graph(lock_code: str) None[source]
Locks the persistent graph in s3.
- Parameters
lock_code – The code that will be used to lock the S3 object.
- Raises
- put_persistent_graph(lock_code: str) None[source]
Upload persistent graph to s3.
- Parameters
lock_code (str) – The code that will be used to lock the S3 object.
- Raises
- set_hook_data(key: str, data: Any) None[source]
Set hook data for the given key.
- Parameters
key – The key to store the hook data in.
data – A dictionary of data to store, as returned from a hook.
- class runway.context.RunwayContext[source]
Bases:
runway.context._base.BaseContextRunway context object.
- __init__(*, command: Optional[RunwayActionTypeDef] = None, deploy_environment: Optional[DeployEnvironment] = None, logger: Union[PrefixAdaptor, RunwayLogger] = <RunwayLogger runway.context._runway (WARNING)>, work_dir: Optional[Path] = None, **_: Any) None[source]
Instantiate class.
- Parameters
command – Runway command/action being run.
deploy_environment – The current deploy environment.
logger – Custom logger.
work_dir – Working directory used by Runway.
- command: Optional[RunwayActionTypeDef]
Runway command/action being run.
- property no_color: bool
Whether to explicitly disable color output.
Primarily applies to IaC being wrapped by Runway.
- property use_concurrent: bool
Whether to use concurrent.futures or not.
Noninteractive is required for concurrent execution to prevent weird user-input behavior.
Python 3 is required because backported futures has issues with ProcessPoolExecutor.
- __new__(**kwargs)
- property boto3_credentials: runway.type_defs.Boto3CredentialsTypeDef
Return a dict of boto3 credentials.
- copy() runway.context.RunwayContext[source]
Copy the contents of this object into a new instance.
- property current_aws_creds: EnvVarsAwsCredentialsTypeDef
AWS credentials from self.env_vars.
- get_session(*, aws_access_key_id: Optional[str] = None, aws_secret_access_key: Optional[str] = None, aws_session_token: Optional[str] = None, profile: Optional[str] = None, region: Optional[str] = None) boto3.session.Session
Create a thread-safe boto3 session.
If
profileis provided, it will take priority.If no credential arguments are passed, will attempt to find them in environment variables.
- Parameters
aws_access_key_id – AWS Access Key ID.
aws_secret_access_key – AWS secret Access Key.
aws_session_token – AWS session token.
profile – The profile for the session.
region – The region for the session.
- Returns
A thread-safe boto3 session.
- property is_interactive: bool
Whether the user should be prompted or not.
Determined by the existed of
CIin the environment.
- property is_noninteractive: bool
Whether the user should be prompted or not.
Determined by the existed of
CIin the environment. Inverse ofis_interactiveproperty.
- env: DeployEnvironment
Object containing information about the environment being deployed to.
- logger: Union[PrefixAdaptor, RunwayLogger]
Custom logger.
- sys_info: SystemInfo
Information about the current system being used to run Runway.
- work_dir: Path
Working directory used by Runway. Should always be a directory named
.runway.
System Information.
- class runway.context.sys_info.OsInfo[source]
Bases:
objectInformation about the operating system running on the current system.
- static __new__(cls, *args: Any, **kwargs: Any) runway.context.sys_info.OsInfo[source]
Create a new instance of class.
This class is a singleton so it will always return the same instance.
- property is_macos: bool
Operating system is macOS.
Does not differentiate between macOS and Darwin.
- classmethod clear_singleton() None[source]
Clear singleton instances.
Intended to only be used for running tests.
- __init__()
- class runway.context.sys_info.SystemInfo[source]
Bases:
objectInformation about the system running Runway.
- static __new__(cls, *args: Any, **kwargs: Any) runway.context.sys_info.SystemInfo[source]
Create a new instance of class.
This class is a singleton so it will always return the same instance.
- property os: runway.context.sys_info.OsInfo
Operating system information.
- classmethod clear_singleton() None[source]
Clear singleton instances.
Intended to only be used for running tests.
- __init__()
Context type definitions.
Core Runway API.
- class runway.core.Runway[source]
Bases:
objectRunway’s core functionality.
- __init__(config: runway.config.RunwayConfig, context: runway.context.RunwayContext) None[source]
Instantiate class.
- Parameters
config – Runway config.
context – Runway context.
- deploy(deployments: Optional[List[RunwayDeploymentDefinition]] = None) None[source]
Deploy action.
- Parameters
deployments – List of deployments to run. If not provided, all deployments in the config will be run.
- destroy(deployments: Optional[List[RunwayDeploymentDefinition]] = None) None[source]
Destroy action.
- Parameters
deployments – List of deployments to run. If not provided, all deployments in the config will be run in reverse.
- get_env_vars(deployments: Optional[List[RunwayDeploymentDefinition]] = None) Dict[str, Any][source]
Get env_vars defined in the config.
- Parameters
deployments – List of deployments to get env_vars from.
- Returns
Resolved env_vars from the deployments.
- init(deployments: Optional[List[RunwayDeploymentDefinition]] = None) None[source]
Init action.
- Parameters
deployments – List of deployments to run. If not provided, all deployments in the config will be run.
- plan(deployments: Optional[List[RunwayDeploymentDefinition]] = None) None[source]
Plan action.
- Parameters
deployments – List of deployments to run. If not provided, all deployments in the config will be run.
- static reverse_deployments(deployments: List[RunwayDeploymentDefinition]) List[RunwayDeploymentDefinition][source]
Reverse deployments and the modules within them.
- Parameters
deployments – List of deployments to reverse.
- Returns
Deployments and modules in reverse order.
- __new__(**kwargs)
Core Runway components.
- class runway.core.components.DeployEnvironment[source]
Bases:
runway.mixins.DelCachedPropMixinRunway deploy environment.
- __init__(*, environ: Optional[Dict[str, str]] = None, explicit_name: Optional[str] = None, ignore_git_branch: bool = False, root_dir: Optional[pathlib.Path] = None) None[source]
Instantiate class.
- Parameters
environ – Environment variables.
explicit_name – Explicitly provide the deploy environment name.
ignore_git_branch – Ignore the git branch when determining the deploy environment name.
root_dir – Root directory of the project.
- property aws_credentials: runway.type_defs.EnvVarsAwsCredentialsTypeDef
Get AWS credentials from environment variables.
- __new__(**kwargs)
- property max_concurrent_cfngin_stacks: int
Max number of CFNgin stacks that can be deployed concurrently.
This property can be set by exporting
RUNWAY_MAX_CONCURRENT_CFNGIN_STACKS. If no value is specified, the value will be constrained based on the underlying graph.- Returns
Value from environment variable or
0.
- property max_concurrent_modules: int
Max number of modules that can be deployed to concurrently.
This property can be set by exporting
RUNWAY_MAX_CONCURRENT_MODULES. If no value is specified,min(61, os.cpu_count())is used.On Windows, this must be equal to or lower than
61.IMPORTANT: When using
parallel_regionsandchild_modulestogether, please consider the nature of their relationship when manually setting this value. (parallel_regions * child_modules)- Returns
Value from environment variable or
min(61, os.cpu_count())
- property max_concurrent_regions: int
Max number of regions that can be deployed to concurrently.
This property can be set by exporting
RUNWAY_MAX_CONCURRENT_REGIONS. If no value is specified,min(61, os.cpu_count())is used.On Windows, this must be equal to or lower than
61.IMPORTANT: When using
parallel_regionsandchild_modulestogether, please consider the nature of their relationship when manually setting this value. (parallel_regions * child_modules)- Returns
Value from environment variable or
min(61, os.cpu_count())
- copy() runway.core.components._deploy_environment.DeployEnvironment[source]
Copy the contents of this object into a new instance.
- Returns
New instance with the same contents.
- Return type
- class runway.core.components.Deployment[source]
Bases:
objectRunway deployment.
- __init__(context: RunwayContext, definition: RunwayDeploymentDefinition, future: Optional[RunwayFutureDefinitionModel] = None, variables: Optional[RunwayVariablesDefinition] = None) None[source]
Instantiate class.
- Parameters
context – Runway context object.
definition – A single deployment definition.
future – Future functionality configuration.
variables – Runway variables.
- property assume_role_config: Dict[str, Union[bool, int, str]]
Parse the definition to get assume role arguments.
- property env_vars_config: Dict[str, str]
Parse the definition to get the correct env_vars configuration.
- plan() None[source]
Plan for the next deploy of the deployment.
High level method for running a deployment.
- run(action: RunwayActionTypeDef, region: str) None[source]
Run a single deployment in a single region.
Low level API access to run a deployment object.
- Parameters
action – Action to run (deploy, destroy, plan, etc.)
region – AWS region to run in.
- validate_account_credentials(context: Optional[RunwayContext] = None) None[source]
Exit if requested deployment account doesn’t match credentials.
- Parameters
context – Context object.
- Raises
SystemExit – AWS Account associated with the current credentials did not match the defined criteria.
- classmethod run_list(action: RunwayActionTypeDef, context: RunwayContext, deployments: List[RunwayDeploymentDefinition], future: RunwayFutureDefinitionModel, variables: RunwayVariablesDefinition) None[source]
Run a list of deployments.
- Parameters
action – Name of action to run.
context – Runway context.
deployments – List of deployments to run.
future – Future definition.
variables – Runway variables for lookup resolution.
- __getitem__(name: str) Any[source]
Make the object subscriptable.
- Parameters
name – Attribute to get.
- __new__(**kwargs)
- class runway.core.components.Module[source]
Bases:
objectRunway module.
- __init__(context: RunwayContext, definition: RunwayModuleDefinition, deployment: RunwayDeploymentDefinition = None, future: RunwayFutureDefinitionModel = None, variables: RunwayVariablesDefinition = None) None[source]
Instantiate class.
- Parameters
context – Runway context object.
definition – A single module definition.
deployment – Deployment that this module is a part of.
future – Future functionality configuration.
variables – Runway variables.
- property child_modules: List[runway.core.components._module.Module]
Return child modules.
- property environment_matches_defined: Optional[bool]
Environment matches one of the defined environments.
Will return None if there is nothing defined for the current environment.
- property environments: RunwayEnvironmentsType
Environments defined for the deployment and module.
- property fqn
Fully qualified name.
- property path: runway.core.components._module_path.ModulePath
Return resolve module path.
- property type: runway.core.components._module_type.RunwayModuleType
Determine Runway module type.
- plan() None[source]
Plan for the next deploy of the module.
High level method for running a module.
- run(action: RunwayActionTypeDef) None[source]
Run a single module.
Low level API access to run a module object.
- Parameters
action – Name of action to run.
- __new__(**kwargs)
- classmethod run_list(action: RunwayActionTypeDef, context: RunwayContext, modules: List[RunwayModuleDefinition], variables: RunwayVariablesDefinition, deployment: RunwayDeploymentDefinition = None, future: Optional[RunwayFutureDefinitionModel] = None) None[source]
Run a list of modules.
- Parameters
action – Name of action to run.
context – Runway context.
modules – List of modules to run.
variables – Variable definition for resolving lookups in the module.
deployment – Deployment the modules are a part of.
future – Future functionality configuration.
- class runway.core.components.ModulePath[source]
Bases:
objectHandler for the
pathfield of a Runway module.- __init__(definition: Optional[Union[pathlib.Path, str]] = None, *, cache_dir: pathlib.Path, deploy_environment: Optional[runway.core.components._deploy_environment.DeployEnvironment] = None) None[source]
Instantiate class.
- Parameters
definition – Path definition.
cache_dir – Directory to use for caching if needed.
deploy_environment – Current deploy environment object.
- property metadata: runway.core.components._module_path.ModulePathMetadataTypeDef
Information that describes the module path.
- property module_root: pathlib.Path
Root directory of the module.
- classmethod parse_obj(obj: Optional[Union[pathlib.Path, runway.config.components.runway._module_def.RunwayModuleDefinition, runway.config.models.runway.RunwayModuleDefinitionModel, str]], *, cache_dir: pathlib.Path, deploy_environment: Optional[runway.core.components._deploy_environment.DeployEnvironment] = None) runway.core.components._module_path.ModulePath[source]
Parse object.
- Parameters
obj – Object to parse.
cache_dir – Directory to use for caching if needed.
deploy_environment – Current deploy environment object.
- Raises
TypeError – Unsupported type provided.
- __new__(**kwargs)
- class runway.core.components.RunwayModuleType[source]
Bases:
objectRunway configuration
typesettings object.The
typeproperty of a Runway configuration can be used to explicitly specify what module type you are intending to deploy.Runway determines the type of module you are trying to deploy in 3 different ways. First, it will check for the
typeproperty as described here, next it will look for a suffix as described in Module Definition, and finally it will attempt to autodetect your module type by scanning the files of the project. If none of those settings produces a valid result an error will occur. The following are valid explicit types:Type
IaC Tool/Framework
cdkAWS CDK
cloudformationCloudFormation
serverlessServerless Framework
terraformTerraform
kubernetesKubernetes
staticEven when specifying a module
typethe module structure needs to be conducive with that type of project. If the files contained within don’t match the type then an error will occur.- __init__(path: Path, class_path: Optional[str] = None, type_str: Optional[RunwayModuleTypeTypeDef] = None) None[source]
Instantiate class.
- Keyword Arguments
path – The required path to the module
class_path – A supplied class_path to override the autodetected one.
type_str – An explicit type to assign to the RunwayModuleType
- __new__(**kwargs)
Runway providers.
Runway AWS objects.
- class runway.core.providers.aws.AccountDetails[source]
Bases:
objectAWS account details.
- __init__(context: Union[CfnginContext, RunwayContext]) None[source]
Instantiate class.
- Parameters
context – Runway context object.
- __new__(**kwargs)
- class runway.core.providers.aws.AssumeRole[source]
Bases:
ContextManager[AssumeRole]Context manager for assuming an AWS role.
- __init__(context: runway.context.RunwayContext, role_arn: Optional[str] = None, duration_seconds: Optional[int] = None, revert_on_exit: bool = True, session_name: Optional[str] = None)[source]
Instantiate class.
- Parameters
context – Runway context object.
role_arn – ARN of role to be assumed.
duration_seconds – Seconds that the assumed role’s credentials will be valid for. (default: 3600)
revert_on_exit – Whether credentials in the environment will be reverted upon exiting the context manager.
session_name – Name to use for the assumed role session. (default: runway)
- __new__(**kwargs)
- __enter__() runway.core.providers.aws._assume_role.AssumeRole[source]
Enter the context manager.
- __exit__(exc_type: Optional[Type[BaseException]], exc_value: Optional[BaseException], traceback: Optional[TracebackType]) None[source]
Exit the context manager.
- class runway.core.providers.aws.BaseResponse[source]
Bases:
runway.utils.BaseModelAnalyse the response from AWS S3 HeadBucket API response.
- Keyword Arguments
Error – Information about a service or networking error.
ResponseMetadata – Information about the request.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- classmethod update_forward_refs(**localns: Any) None
Try to update ForwardRefs on fields based on this Model, globalns and localns.
- error: runway.core.providers.aws._response.ResponseError
Information about a service or networking error.
- metadata: runway.core.providers.aws._response.ResponseMetadata
Information about the request.
- class runway.core.providers.aws.ResponseError[source]
Bases:
runway.utils.BaseModelAnalyse the response from AWS S3 HeadBucket API response.
- Keyword Arguments
Code – A unique short code representing the error that was emitted.
Message – A longer human readable error message.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.core.providers.aws.ResponseMetadata[source]
Bases:
runway.utils.BaseModelAnalyse the response from AWS S3 HeadBucket API response.
- Keyword Arguments
HostId – Host ID data.
HTTPHeaders – A map of response header keys and their respective values.
HTTPStatusCode – The HTTP status code of the response (e.g., 200, 404).
RequestId – The unique request ID associated with the response. Log this value when debugging requests for AWS support.
RetryAttempts – The number of retries that were attempted before the request was completed.
- request_id: str
The unique request ID associated with the response. Log this value when debugging requests for AWS support.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
AWS S3 objects.
- class runway.core.providers.aws.s3.Bucket[source]
Bases:
runway.mixins.DelCachedPropMixinAWS S3 bucket.
- __init__(context: Union[CfnginContext, RunwayContext], name: str, region: Optional[str] = None) None[source]
Instantiate class.
- Parameters
context – Current context object.
name – The name of the bucket.
region – The bucket’s region.
- property client: S3Client
Create or reuse a boto3 client.
- property head
Check if a bucket exists and you have permission to access it.
To use this operation, the user must have permissions to perform the
s3:ListBucketaction.This is a low level action that returns the raw result of the request.
- property session: boto3.Session
Create cached boto3 session.
- create(**kwargs: Any) Optional[CreateBucketOutputTypeDef][source]
Create an S3 Bucket if it does not already exist.
Bucket creation will be skipped if it already exists or access is forbidden.
Keyword arguments are passed directly to the boto3 method.
- Returns
boto3 response.
- format_bucket_path_uri(*, key: Optional[str] = None, prefix: Optional[str] = None) str[source]
Format bucket path URI.
- Parameters
key – S3 object key.
prefix – Directory tree to append to key.
- Returns
S3 bucket URI in
s3://{bucket-name}/{prefix}/{key}format
- get_versioning() GetBucketVersioningOutputTypeDef[source]
Get the versioning state of a bucket.
To retrieve the versioning state of a bucket, you must be the bucket owner.
- Returns
The current versioning state of the bucket containing
StatusandMFADelete(only if this has ever been configured).
- sync_from_local(src_directory: str, *, delete: bool = False, exclude: Optional[List[str]] = None, follow_symlinks: bool = False, include: Optional[List[str]] = None, prefix: Optional[str] = None) None[source]
Sync local directory to the S3 Bucket.
- Parameters
src_directory – Local directory to sync to S3.
delete – If true, files that exist in the destination but not in the source are deleted.
exclude – List of patterns for files/objects to exclude.
follow_symlinks – If symlinks should be followed.
include – List of patterns for files/objects to explicitly include.
prefix – Optional prefix to append to synced objects.
- sync_to_local(dest_directory: str, *, delete: bool = False, exclude: Optional[List[str]] = None, follow_symlinks: bool = False, include: Optional[List[str]] = None, prefix: Optional[str] = None) None[source]
Sync S3 bucket to local directory.
- Parameters
dest_directory – Local directory to sync S3 objects to.
delete – If true, files that exist in the destination but not in the source are deleted.
exclude – List of patterns for files/objects to exclude.
follow_symlinks – If symlinks should be followed.
include – List of patterns for files/objects to explicitly include.
prefix – Optional prefix to append to synced objects.
- __new__(**kwargs)
AWS S3 exceptions.
- exception runway.core.providers.aws.s3.exceptions.BucketAccessDeniedError[source]
Bases:
runway.exceptions.RunwayErrorAccess denied to S3 Bucket.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.core.providers.aws.s3.exceptions.BucketNotFoundError[source]
Bases:
runway.exceptions.RunwayErrorS3 Bucket not found.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.core.providers.aws.s3.exceptions.S3ObjectDoesNotExistError[source]
Bases:
runway.exceptions.RunwayErrorRequired S3 object does not exist.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
Type definitions.
Classes for interacting with dependency managers using subprocesses.
- class runway.dependency_managers.Pip[source]
Bases:
runway.dependency_managers.base_classes.DependencyManagerpip CLI interface.
- CONFIG_FILES: Final[Tuple[Literal['requirements.txt']]] = ('requirements.txt',)
Configuration files used by pip.
- EXECUTABLE: Final[Literal['pip']] = 'pip'
CLI executable.
- property python_version: runway.utils._version.Version
Python version where pip is installed (
<major>.<minor>only).
- property version: runway.utils._version.Version
pip version.
- classmethod dir_is_project(directory: StrPath, **kwargs: Any) bool[source]
Determine if the directory contains a project for this dependency manager.
- Parameters
directory – Directory to check.
- classmethod generate_install_command(*, cache_dir: Optional[StrPath] = None, no_cache_dir: bool = False, no_deps: bool = False, requirements: StrPath, target: StrPath) List[str][source]
Generate the command that when run will install dependencies.
This method is exposed to easily format the command to be run by with a subprocess or within a Docker container.
- Parameters
cache_dir – Store the cache data in the provided directory.
no_cache_dir – Disable the cache.
no_deps – Don’t install package dependencies.
requirements – Path to a
requirements.txtfile.target – Path to a directory where dependencies will be installed.
- __init__(context: Union[CfnginContext, RunwayContext], cwd: StrPath) None
Instantiate class.
- Parameters
context – CFNgin or Runway context object.
cwd – Working directory where commands will be run.
- __new__(**kwargs)
- static convert_to_cli_arg(arg_name: str, *, prefix: str = '--') str
Convert string kwarg name into a CLI argument.
- install(*, cache_dir: Optional[StrPath] = None, extend_args: Optional[List[str]] = None, no_cache_dir: bool = False, no_deps: bool = False, requirements: StrPath, target: StrPath) Path[source]
Install dependencies to a target directory.
- Parameters
cache_dir – Store the cache data in the provided directory.
extend_args – Optional list of extra arguments to pass to
pip install. This value will not be parsed or sanitized in any way - it will be used as is. It is the user’s responsibility to ensure that there are no overlapping arguments between this list and the arguments that are automatically generated.no_cache_dir – Disable the cache.
no_deps – Don’t install package dependencies.
requirements – Path to a
requirements.txtfile.target – Path to a directory where dependencies will be installed.
- Raises
PipInstallFailedError – The subprocess used to run the commend exited with an error.
- static list2cmdline(split_command: Iterable[str]) str
Combine a list of strings into a string that can be run as a command.
Handles multi-platform differences.
- ctx: Union[CfnginContext, RunwayContext]
CFNgin or Runway context object.
- cwd: Path
Working directory where commands will be run.
- classmethod generate_command(command: Union[List[str], str], **kwargs: Optional[Union[bool, Iterable[str], str]]) List[str][source]
Generate command to be executed and log it.
- Parameters
command – Command to run.
args – Additional args to pass to the command.
- Returns
The full command to be passed into a subprocess.
- exception runway.dependency_managers.PipInstallFailedError[source]
Bases:
runway.exceptions.RunwayErrorPip install failed.
- __init__(*args: Any, **kwargs: Any) None[source]
Instantiate class. All args/kwargs are passed to parent method.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- class runway.dependency_managers.Pipenv[source]
Bases:
runway.dependency_managers.base_classes.DependencyManagerPipenv dependency manager.
- CONFIG_FILES: Final[Tuple[Literal['Pipfile'], Literal['Pipfile.lock']]] = ('Pipfile', 'Pipfile.lock')
Configuration files used by pipenv.
- EXECUTABLE: Final[Literal['pipenv']] = 'pipenv'
CLI executable.
- property version: runway.utils._version.Version
pipenv version.
- __init__(context: Union[CfnginContext, RunwayContext], cwd: StrPath) None
Instantiate class.
- Parameters
context – CFNgin or Runway context object.
cwd – Working directory where commands will be run.
- __new__(**kwargs)
- static convert_to_cli_arg(arg_name: str, *, prefix: str = '--') str
Convert string kwarg name into a CLI argument.
- classmethod dir_is_project(directory: StrPath, **_Pipenv__kwargs: Any) bool[source]
Determine if the directory contains a project for this dependency manager.
- Parameters
directory – Directory to check.
- classmethod generate_command(command: Union[List[str], str], **kwargs: Optional[Union[bool, Iterable[str], str]]) List[str]
Generate command to be executed and log it.
- Parameters
command – Command to run.
args – Additional args to pass to the command.
- Returns
The full command to be passed into a subprocess.
- static list2cmdline(split_command: Iterable[str]) str
Combine a list of strings into a string that can be run as a command.
Handles multi-platform differences.
- ctx: Union[CfnginContext, RunwayContext]
CFNgin or Runway context object.
- cwd: Path
Working directory where commands will be run.
- exception runway.dependency_managers.PipenvExportFailedError[source]
Bases:
runway.exceptions.RunwayErrorPipenv export failed to produce a
requirements.txtfile.- __init__(*args: Any, **kwargs: Any) None[source]
Instantiate class. All args/kwargs are passed to parent method.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.dependency_managers.PipenvNotFoundError[source]
Bases:
runway.exceptions.RunwayErrorPipenv not installed or found in $PATH.
- __init__(*args: Any, **kwargs: Any) None[source]
Instantiate class. All args/kwargs are passed to parent method.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- class runway.dependency_managers.Poetry[source]
Bases:
runway.dependency_managers.base_classes.DependencyManagerPoetry dependency manager.
- CONFIG_FILES: Final[Tuple[Literal['poetry.lock'], Literal['pyproject.toml']]] = ('poetry.lock', 'pyproject.toml')
Configuration files used by poetry.
- EXECUTABLE: Final[Literal['poetry']] = 'poetry'
CLI executable.
- property version: runway.utils._version.Version
poetry version.
- __init__(context: Union[CfnginContext, RunwayContext], cwd: StrPath) None
Instantiate class.
- Parameters
context – CFNgin or Runway context object.
cwd – Working directory where commands will be run.
- __new__(**kwargs)
- static convert_to_cli_arg(arg_name: str, *, prefix: str = '--') str
Convert string kwarg name into a CLI argument.
- classmethod dir_is_project(directory: StrPath, **_Poetry__kwargs: Any) bool[source]
Determine if the directory contains a project for this dependency manager.
- Parameters
directory – Directory to check.
- classmethod generate_command(command: Union[List[str], str], **kwargs: Optional[Union[bool, Iterable[str], str]]) List[str]
Generate command to be executed and log it.
- Parameters
command – Command to run.
args – Additional args to pass to the command.
- Returns
The full command to be passed into a subprocess.
- static list2cmdline(split_command: Iterable[str]) str
Combine a list of strings into a string that can be run as a command.
Handles multi-platform differences.
- ctx: Union[CfnginContext, RunwayContext]
CFNgin or Runway context object.
- cwd: Path
Working directory where commands will be run.
- export(*, dev: bool = False, extras: Optional[List[str]] = None, output: StrPath, output_format: str = 'requirements.txt', with_credentials: bool = True, without_hashes: bool = True) Path[source]
Export the lock file to other formats.
- Parameters
dev – Include development dependencies.
extras – Extra sets of dependencies to include.
output – Path to the output file.
output_format – The format to export to.
with_credentials – Include credentials for extra indices.
without_hashes – Exclude hashes from the exported file.
- Returns
Path to the output file.
- exception runway.dependency_managers.PoetryExportFailedError[source]
Bases:
runway.exceptions.RunwayErrorPoetry export failed to produce a
requirements.txtfile.- __init__(output: str, *args: Any, **kwargs: Any) None[source]
Instantiate class. All args/kwargs are passed to parent method.
- Parameters
output – The output from running
poetry export.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.dependency_managers.PoetryNotFoundError[source]
Bases:
runway.exceptions.RunwayErrorPoetry not installed or found in $PATH.
- __init__(*args: Any, **kwargs: Any) None[source]
Instantiate class. All args/kwargs are passed to parent method.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
Base classes for dependency managers.
- class runway.dependency_managers.base_classes.DependencyManager[source]
Bases:
runway.mixins.CliInterfaceMixinDependency manager for the AWS Lambda runtime.
Dependency managers are interfaced with via subprocess to ensure that the correct version is being used. This is primarily target at Python dependency manager that we could import and use directly.
- __init__(context: Union[CfnginContext, RunwayContext], cwd: StrPath) None[source]
Instantiate class.
- Parameters
context – CFNgin or Runway context object.
cwd – Working directory where commands will be run.
- ctx: Union[CfnginContext, RunwayContext]
CFNgin or Runway context object.
- cwd: Path
Working directory where commands will be run.
- property version: Version
Get executable version.
- __new__(**kwargs)
- static convert_to_cli_arg(arg_name: str, *, prefix: str = '--') str
Convert string kwarg name into a CLI argument.
- classmethod dir_is_project(directory: StrPath, **_DependencyManager__kwargs: Any) bool[source]
Determine if the directory contains a project for this dependency manager.
- Parameters
directory – Directory to check.
- classmethod generate_command(command: Union[List[str], str], **kwargs: Optional[Union[bool, Iterable[str], str]]) List[str]
Generate command to be executed and log it.
- Parameters
command – Command to run.
args – Additional args to pass to the command.
- Returns
The full command to be passed into a subprocess.
Base module for environment managers.
- runway.env_mgr.handle_bin_download_error(exc: URLError, name: str) None[source]
Give user info about their failed download.
- Raises
SystemExit – Always raised after logging reason.
- class runway.env_mgr.EnvManager[source]
Bases:
runway.mixins.DelCachedPropMixinBase environment manager class.
- binPath to the binary of the current version.
- env_dir_name
Name of the directory within the users home directory where binary versions will be stored.
- Type
- path
The current working directory.
- Type
- __init__(bin_name: str, dir_name: str, path: Optional[pathlib.Path] = None) None[source]
Initialize class.
- Parameters
bin_name – Name of the binary file (e.g. kubectl)
dir_name – Name of the directory within the users home directory where binary versions will be stored.
path – The current working directory.
- property bin: pathlib.Path
Path to the version binary.
- Returns
Path
- property env_dir: pathlib.Path
Return the directory used to store version binaries.
- property versions_dir: pathlib.Path
Return the directory used to store binary.
When first used, the existence of the directory is checked and it is created if needed.
- __new__(**kwargs)
- property version_file: Optional[pathlib.Path]
Find and return a “<bin version file>” file if one is present.
- Returns
Path to the <bin> version file.
Kubectl version management.
- runway.env_mgr.kbenv.verify_kb_release(kb_url: str, download_dir: str, filename: str) None[source]
Compare checksum and exit if it doesn’t match.
Different releases provide varying checksum files. To account for this, start at SHA512 and work down to the first available checksum.
requests is used for downloading these small files because of difficulty in getting 404 status from urllib on py2. Once py2 support is dropped, downloads can be moved to urllib.
https://stackoverflow.com/questions/1308542/how-to-catch-404-error-in-urllib-urlretrieve
- runway.env_mgr.kbenv.download_kb_release(version: str, versions_dir: Path, kb_platform: Optional[str] = None, arch: Optional[str] = None) None[source]
Download kubectl and return path to it.
- class runway.env_mgr.kbenv.KBEnvManager[source]
Bases:
runway.env_mgr.EnvManagerkubectl version management.
Designed to be compatible with https://github.com/alexppg/kbenv.
- __init__(path: Optional[Path] = None, *, overlay_path: Optional[Path] = None) None[source]
Initialize class.
- Parameters
path – Module path.
overlay_path – Path to Kustomize overlay.
- property version: Optional[runway.utils._version.Version]
Terraform version.
- property version_file: Optional[Path]
Find and return a “.kubectl-version” file if one is present.
- Returns
Path to the kubectl version file.
- get_version_from_file(file_path: Optional[Path] = None) Optional[str][source]
Get kubectl version from a file.
- Parameters
file_path – Path to file that will be read.
- list_installed() Generator[Path, None, None][source]
List installed versions of kubectl.
Only lists versions of kubectl that have been installed by an instance if this class or by kbenv.
- set_version(version: str) None[source]
Set current version.
Clears cached values as needed.
- Parameters
version – Version string. Must be in the format of
v<major>.<minor>.<patch>with an optional-<prerelease>.
- classmethod parse_version_string(version: str) runway.utils._version.Version[source]
Parse version string into a
Version.- Parameters
version – Version string to parse. Must be in the format of
<major>.<minor>.<patch>with an optional-<prerelease>.
- __new__(**kwargs)
- property bin: pathlib.Path
Path to the version binary.
- Returns
Path
- property env_dir: pathlib.Path
Return the directory used to store version binaries.
- uninstall(version: Union[str, Version]) bool
Uninstall a version of the managed binary.
- Parameters
version – Version of binary to uninstall.
- Returns
Whether a version of the binary was uninstalled or not.
- property versions_dir: pathlib.Path
Return the directory used to store binary.
When first used, the existence of the directory is checked and it is created if needed.
Terraform version management.
- runway.env_mgr.tfenv.download_tf_release(version: str, versions_dir: Path, command_suffix: str, tf_platform: Optional[str] = None, arch: Optional[str] = None) None[source]
Download Terraform archive and return path to it.
- runway.env_mgr.tfenv.get_available_tf_versions(include_prerelease: bool = False) List[str][source]
Return available Terraform versions.
- runway.env_mgr.tfenv.get_latest_tf_version(include_prerelease: bool = False) str[source]
Return latest Terraform version.
- runway.env_mgr.tfenv.load_terraform_module(parser: ModuleType, path: Path) Dict[str, Any][source]
Load all Terraform files in a module into one dict.
- Parameters
parser (Union[hcl, hcl2]) – Parser to use when loading files.
path – Terraform module path. All Terraform files in the path will be loaded.
- class runway.env_mgr.tfenv.TFEnvManager[source]
Bases:
runway.env_mgr.EnvManagerTerraform version management.
Designed to be compatible with https://github.com/tfutils/tfenv.
- property terraform_block: Dict[str, Any]
Collect Terraform configuration blocks from a Terraform module.
- property version: Optional[runway.utils._version.Version]
Terraform version.
- property version_file: Optional[Path]
Find and return a “.terraform-version” file if one is present.
- Returns
Path to the Terraform version file.
- get_min_required() str[source]
Get the defined minimum required version of Terraform.
- Returns
The minimum required version as defined in the module.
- get_version_from_file(file_path: Optional[Path] = None) Optional[str][source]
Get Terraform version from a file.
- Parameters
file_path – Path to file that will be read.
- list_installed() Generator[Path, None, None][source]
List installed versions of Terraform.
Only lists versions of Terraform that have been installed by an instance if this class or by tfenv.
- set_version(version: str) None[source]
Set current version.
Clears cached values as needed.
- Parameters
version – Version string. Must be in the format of
<major>.<minor>.<patch>with an optional-<prerelease>.
- classmethod get_version_from_executable(bin_path: Union[Path, str], *, cwd: Optional[Union[Path, str]] = None, env: Optional[Dict[str, str]] = None) Optional[Version][source]
Get Terraform version from an executable.
- Parameters
bin_path – Path to the Terraform binary to retrieve the version from.
cwd – Current working directory to use when calling the executable.
env – Environment variable overrides.
- classmethod parse_version_string(version: str) runway.utils._version.Version[source]
Parse version string into a
Version.- Parameters
version – Version string to parse. Must be in the format of
<major>.<minor>.<patch>with an optional-<prerelease>.
- __new__(**kwargs)
- property bin: pathlib.Path
Path to the version binary.
- Returns
Path
- property env_dir: pathlib.Path
Return the directory used to store version binaries.
- uninstall(version: Union[str, Version]) bool
Uninstall a version of the managed binary.
- Parameters
version – Version of binary to uninstall.
- Returns
Whether a version of the binary was uninstalled or not.
- property versions_dir: pathlib.Path
Return the directory used to store binary.
When first used, the existence of the directory is checked and it is created if needed.
Empty init for python import traversal.
Runway lookup handlers.
Base class for lookup handlers.
- class runway.lookups.handlers.base.LookupHandler[source]
Bases:
objectBase class for lookup handlers.
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str][source]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any[source]
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod handle(_LookupHandler__value: str, context: Union[CfnginContext, RunwayContext], *_LookupHandler__args: Any, provider: Optional[Provider] = None, **_LookupHandler__kwargs: Any) Any[source]
Perform the lookup.
- Parameters
__value – Parameter(s) given to the lookup.
context – The current context object.
provider – CFNgin AWS provider.
- classmethod parse(value: str) Tuple[str, Dict[str, str]][source]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any[source]
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any[source]
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
- __init__()
- __new__(**kwargs)
Retrieve a value from CloudFormation Stack Outputs.
The query syntax for this lookup is <stack-name>.<output-name>.
When specifying the output name, be sure to use the Logical ID of
the output; not the Export.Name.
- class runway.lookups.handlers.cfn.OutputQuery[source]
Bases:
NamedTupleOutput query NamedTuple.
- __init__()
- static __new__(_cls, stack_name: str, output_name: str)
Create new instance of OutputQuery(stack_name, output_name)
- count(value, /)
Return number of occurrences of value.
- index(value, start=0, stop=9223372036854775807, /)
Return first index of value.
Raises ValueError if the value is not present.
- class runway.lookups.handlers.cfn.CfnLookup[source]
Bases:
runway.lookups.handlers.base.LookupHandlerCloudFormation Stack Output lookup.
- TYPE_NAME: Final[typing_extensions.Literal[cfn]] = 'cfn'
Name that the Lookup is registered as.
- static should_use_provider(args: Dict[str, str], provider: Optional[Provider]) bool[source]
Determine if the provider should be used for the lookup.
This will open happen when the lookup is used with CFNgin.
- Parameters
args – Parsed arguments provided to the lookup.
provider – CFNgin provider.
- static get_stack_output(client: CloudFormationClient, query: OutputQuery) str[source]
Get CloudFormation Stack output.
- Parameters
client – Boto3 CloudFormation client.
query – What to get.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod handle(value: str, context: Union[CfnginContext, RunwayContext], *, provider: Optional[Provider] = None, **_: Any) Any[source]
Retrieve a value from CloudFormation Stack outputs.
- Parameters
value – The value passed to the Lookup.
context – The current context object.
provider – AWS provider.
- Returns
Result of the query.
- Raises
OutputDoesNotExist – Output does not exist on the Stack provided and default was not provided.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
Retrieve a value from AWS Elastic Container Registry (ECR).
- class runway.lookups.handlers.ecr.EcrLookup[source]
Bases:
runway.lookups.handlers.base.LookupHandlerECR Lookup.
- TYPE_NAME: Final[typing_extensions.Literal[ecr]] = 'ecr'
Name that the Lookup is registered as.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod handle(value: str, context: Union[CfnginContext, RunwayContext], *_EcrLookup__args: Any, **_EcrLookup__kwargs: Any) Any[source]
Retrieve a value from AWS Elastic Container Registry (ECR).
- Parameters
value – The value passed to the Lookup.
context – The current context object.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
Retrieve a value from an environment variable.
- class runway.lookups.handlers.env.EnvLookup[source]
Bases:
runway.lookups.handlers.base.LookupHandlerEnvironment variable Lookup.
- TYPE_NAME: Final[typing_extensions.Literal[env]] = 'env'
Name that the Lookup is registered as.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod handle(value: str, context: Union[CfnginContext, RunwayContext], *_EnvLookup__args: Any, **_EnvLookup__kwargs: Any) Any[source]
Retrieve an environment variable.
The value is retrieved from a copy of the current environment variables that is saved to the context object. These environment variables are manipulated at runtime by Runway to fill in additional values such as
DEPLOY_ENVIRONMENTandAWS_REGIONto match the current execution.- Parameters
value – The value passed to the Lookup.
context – The current context object.
- Raises
ValueError – Unable to find a value for the provided query and a default value was not provided.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
Generate a random string.
- class runway.lookups.handlers.random_string.ArgsDataModel[source]
Bases:
runway.utils.BaseModelArguments data model.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.lookups.handlers.random_string.RandomStringLookup[source]
Bases:
runway.lookups.handlers.base.LookupHandlerRandom string lookup.
- TYPE_NAME: Final[typing_extensions.Literal[random.string]] = 'random.string'
Name that the Lookup is registered as.
- static calculate_char_set(args: runway.lookups.handlers.random_string.ArgsDataModel) str[source]
Calculate character set from the provided arguments.
- static generate_random_string(char_set: Sequence[str], length: int) str[source]
Generate a random string of a set length from a set of characters.
- classmethod ensure_has_one_of(args: runway.lookups.handlers.random_string.ArgsDataModel, value: str) bool[source]
Ensure value has at least one of each required character.
- Parameters
args – Hook args.
value – Value to check.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod handle(value: str, context: Union[CfnginContext, RunwayContext], *_RandomStringLookup__args: Any, **_RandomStringLookup__kwargs: Any) Any[source]
Generate a random string.
- Parameters
value – The value passed to the Lookup.
context – The current context object.
- Raises
ValueError – Unable to find a value for the provided query and a default value was not provided.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
Retrieve a value from SSM Parameter Store.
- class runway.lookups.handlers.ssm.SsmLookup[source]
Bases:
runway.lookups.handlers.base.LookupHandlerSSM Parameter Store Lookup.
- TYPE_NAME: Final[typing_extensions.Literal[ssm]] = 'ssm'
Name that the Lookup is registered as.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod handle(value: str, context: Union[CfnginContext, RunwayContext], *_SsmLookup__args: Any, **_SsmLookup__kwargs: Any) Any[source]
Retrieve a value from SSM Parameter Store.
- Parameters
value – The value passed to the Lookup.
context – The current context object.
- Raises
ParameterNotFound – Parameter not found in SSM and a default value was not provided.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
Retrieve a variable from the variables file or definition.
- class runway.lookups.handlers.var.VarLookup[source]
Bases:
runway.lookups.handlers.base.LookupHandlerVariable definition Lookup.
- TYPE_NAME: Final[typing_extensions.Literal[var]] = 'var'
Name that the Lookup is registered as.
- __init__()
- __new__(**kwargs)
- classmethod dependencies(_LookupHandler__lookup_query: VariableValue) Set[str]
Calculate any dependencies required to perform this lookup.
Note that lookup_query may not be (completely) resolved at this time.
- classmethod format_results(value: Any, get: Optional[str] = None, load: Optional[str] = None, transform: Optional[typing_extensions.Literal[bool, str]] = None, **kwargs: Any) Any
Format results to be returned by a lookup.
- Parameters
value – Data collected by the Lookup.
get – Nested value to get from a dictionary like object.
load – Parser to use to parse a formatted string before the
getandtransformmethod.transform – Convert the final value to a different data type before returning it.
- Raises
TypeError – If
getis provided but the value value is not a dictionary like object.
Runs the following actions in order:
load()ifloadis provided.runway.util.MutableMap.find()ordict.get()depending on the data type ifgetis provided.Convert null value string to
NoneTypeobject. This includes string values of “None” and “null”. This conversion is case insensitive.transform()iftransformis provided.
- classmethod handle(value: str, *_VarLookup__args: Any, variables: MutableMap, **_VarLookup__kwargs: Any) Any[source]
Retrieve a variable from the variable definition.
The value is retrieved from the variables passed to Runway using either a variables file or the
variablesdirective of the config file.- Parameters
value – The value passed to the Lookup.
variables – The resolved variables pass to Runway.
- Raises
ValueError – Unable to find a value for the provided query and a default value was not provided.
- classmethod load(value: Any, parser: Optional[str] = None, **kwargs: Any) Any
Load a formatted string or object into a python data type.
First action taken in
format_results(). If a lookup needs to handling loading data to process it before it entersformat_results(), is should useargs.pop('load')to prevent the data from being loaded twice.- Parameters
value – What is being loaded.
parser – Name of the parser to use.
- Returns
The loaded value.
- classmethod parse(value: str) Tuple[str, Dict[str, str]]
Parse the value passed to a lookup in a standardized way.
- Parameters
value – The raw value passed to a lookup.
- Returns
The lookup query and a dict of arguments
- classmethod transform(value: Any, *, to_type: Optional[typing_extensions.Literal[bool, str]] = 'str', **kwargs: Any) Any
Transform the result of a lookup into another datatype.
Last action taken in
format_results(). If a lookup needs to handling transforming the data in a way that the base class can’t support it should overwrite this method of the base class to register different transform methods.- Parameters
value – What is to be transformed.
to_type – The type the value will be transformed into.
- Returns
The transformed value.
Register test handlers.
Classes and utilities for working with each Runway module type.
Runway Static Site Module.
- class runway.module.staticsite.StaticSite[source]
Bases:
runway.module.base.RunwayModuleStatic website Runway Module.
- __init__(context: RunwayContext, *, explicitly_enabled: Optional[bool] = False, logger: RunwayLogger = <RunwayLogger runway.module.staticsite.handler (WARNING)>, module_root: Path, name: Optional[str] = None, options: Optional[Union[Dict[str, Any], ModuleOptions]] = None, parameters: Optional[Dict[str, Any]] = None, **_: Any) None[source]
Instantiate class.
- Parameters
context – Runway context object for the current session.
explicitly_enabled – Whether or not the module is explicitly enabled. This is can be set in the event that the current environment being deployed to matches the defined environments of the module/deployment.
logger – Used to write logs.
module_root – Root path of the module.
name – Name of the module.
options – Options passed to the module class from the config as
optionsormodule_optionsif coming from the deployment level.parameters – Values to pass to the underlying infrastructure as code tool that will alter the resulting infrastructure being deployed. Used to templatize IaC.
- property sanitized_name: str
Sanitized name safe to use in a CloudFormation Stack name.
Errors are usually caused here by a
.in the name. This unintelligently replaces.with-.If issues are still encountered, we can check against the regex of
(?=^.{1,128}$)^[a-zA-Z][-a-zA-Z0-9_]+$.
- __new__(**kwargs)
Runway Static Site Module options.
- class runway.module.staticsite.options.RunwayStaticSiteExtraFileDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway static site Module extra_files option item.
- content_type
An explicit content type for the file. If not provided, will attempt to determine based on the name provided.
- Type
Optional[str]
- content
Inline content that will be used as the file content. This or
filemust be provided.- Type
Any
- file
Path to an existing file. The content of this file will be uploaded to the static site S3 bucket using the name as the object key. This or
contentmust be provided.- Type
Optional[pathlib.Path]
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.module.staticsite.options.RunwayStaticSiteModuleOptionsDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway static site Module options.
- build_output
Directory where build output is placed. Defaults to current working directory.
- Type
- extra_files
List of files that should be uploaded to S3 after the build. Used to dynamically create or select file.
- pre_build_steps
Commands to be run prior to the build process.
- source_hashing
Overrides for source hash calculation and tracking.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.module.staticsite.options.RunwayStaticSitePreBuildStepDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway static site Module pre_build_steps option item.
- cwd
The working directory for the subprocess running the command. If not provided, the current working directory is used.
- Type
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.module.staticsite.options.RunwayStaticSiteSourceHashingDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway static site Module source_hashing option.
- directories
Explicitly provide the directories to use when calculating the hash. If not provided, will default to the root of the module.
- enabled
Enable source hashing. If not enabled, build and upload will occur on every deploy.
- Type
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.module.staticsite.options.RunwayStaticSiteSourceHashingDirectoryDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway static site Module source_hashing.directory option item.
- path
Path to files to include in the hash.
- Type
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.module.staticsite.options.StaticSiteOptions[source]
Bases:
runway.module.base.ModuleOptionsStatic site options.
- build_output
Directory where build output is placed. Defaults to current working directory.
- build_steps
List of commands to run to build the static site.
- data
Options parsed into a data model.
- extra_files
List of files that should be uploaded to S3 after the build. Used to dynamically create or select file.
- pre_build_steps
Commands to be run prior to the build process.
- source_hashing
Overrides for source hash calculation and tracking.
- __init__(data: runway.module.staticsite.options.models.RunwayStaticSiteModuleOptionsDataModel) None[source]
Instantiate class.
- classmethod parse_obj(obj: object) runway.module.staticsite.options.components.StaticSiteOptions[source]
Parse options definition and return an options object.
- Parameters
obj – Object to parse.
- __new__(**kwargs)
Runway Static Site Module options component classes.
- class runway.module.staticsite.options.components.StaticSiteOptions[source]
Bases:
runway.module.base.ModuleOptionsStatic site options.
- build_output
Directory where build output is placed. Defaults to current working directory.
- build_steps
List of commands to run to build the static site.
- data
Options parsed into a data model.
- extra_files
List of files that should be uploaded to S3 after the build. Used to dynamically create or select file.
- pre_build_steps
Commands to be run prior to the build process.
- source_hashing
Overrides for source hash calculation and tracking.
- __init__(data: runway.module.staticsite.options.models.RunwayStaticSiteModuleOptionsDataModel) None[source]
Instantiate class.
- classmethod parse_obj(obj: object) runway.module.staticsite.options.components.StaticSiteOptions[source]
Parse options definition and return an options object.
- Parameters
obj – Object to parse.
- __new__(**kwargs)
Runway static site Module options.
- class runway.module.staticsite.options.models.RunwayStaticSiteExtraFileDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway static site Module extra_files option item.
- content_type
An explicit content type for the file. If not provided, will attempt to determine based on the name provided.
- Type
Optional[str]
- content
Inline content that will be used as the file content. This or
filemust be provided.- Type
Any
- file
Path to an existing file. The content of this file will be uploaded to the static site S3 bucket using the name as the object key. This or
contentmust be provided.- Type
Optional[pathlib.Path]
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.module.staticsite.options.models.RunwayStaticSitePreBuildStepDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway static site Module pre_build_steps option item.
- cwd
The working directory for the subprocess running the command. If not provided, the current working directory is used.
- Type
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.module.staticsite.options.models.RunwayStaticSiteSourceHashingDirectoryDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway static site Module source_hashing.directory option item.
- path
Path to files to include in the hash.
- Type
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.module.staticsite.options.models.RunwayStaticSiteSourceHashingDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway static site Module source_hashing option.
- directories
Explicitly provide the directories to use when calculating the hash. If not provided, will default to the root of the module.
- enabled
Enable source hashing. If not enabled, build and upload will occur on every deploy.
- Type
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.module.staticsite.options.models.RunwayStaticSiteModuleOptionsDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway static site Module options.
- build_output
Directory where build output is placed. Defaults to current working directory.
- Type
- extra_files
List of files that should be uploaded to S3 after the build. Used to dynamically create or select file.
- pre_build_steps
Commands to be run prior to the build process.
- source_hashing
Overrides for source hash calculation and tracking.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
Runway Static Site Module parameters.
- class runway.module.staticsite.parameters.RunwayStaticSiteCustomErrorResponseDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway stat site Module staticsite_custom_error_responses parameter item.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.module.staticsite.parameters.RunwayStaticSiteLambdaFunctionAssociationDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway stat site Module staticsite_lambda_function_associations parameter item.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.module.staticsite.parameters.RunwayStaticSiteModuleParametersDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway static site Module parameters.
- acmcert_arn
The certificate arn used for any alias domains supplied. This is a requirement when supplying any custom domain.
- Type
Optional[str]
- additional_redirect_domains
Additional domains (beyond the
aliasesdomains or the CloudFront URL if no aliases are provided) that will be authorized by the Auth@Edge UserPool AppClient.- Type
List[str]
- auth_at_edge
Auth@Edge make the static site private by placing it behind an authorization wall.
- Type
- compress
Whether the CloudFront default cache behavior will automatically compress certain files.
- Type
- cookie_settings
The default cookie settings for retrieved tokens and generated nonce’s.
- custom_error_responses
Define custom error responses.
- lambda_function_associations
This allows the user to deploy custom Lambda@Edge associations with their pre-build function versions.
- oauth_scopes
Scope is a mechanism in OAuth 2.0 to limit an application’s access to a user’s account.
- Type
List[str]
- redirect_path_auth_refresh
The path that a user is redirected to when their authorization tokens have expired (1 hour).
- Type
- required_group
Name of Cognito User Pool group of which users must be a member to be granted access to the site. If
None, allows all UserPool users to have access.- Type
Optional[str]
- rewrite_directory_index
Deploy a Lambda@Edge function designed to rewrite directory indexes.
- Type
Optional[str]
- role_boundary_arn
Defines an IAM Managed Policy that will be set as the permissions boundary for any IAM Roles created to support the site.
- Type
Optional[str]
- supported_identity_providers
A comma delimited list of the User Pool client identity providers.
- Type
List[str]
- user_pool_arn
The ARN of a pre-existing Cognito User Pool to use with Auth@Edge.
- Type
Optional[str]
- web_acl
The ARN of a web access control list (web ACL) to associate with the CloudFront Distribution.
- Type
Optional[str]
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
Runway static site Module parameters.
- class runway.module.staticsite.parameters.models.RunwayStaticSiteCustomErrorResponseDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway stat site Module staticsite_custom_error_responses parameter item.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.module.staticsite.parameters.models.RunwayStaticSiteLambdaFunctionAssociationDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway stat site Module staticsite_lambda_function_associations parameter item.
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.module.staticsite.parameters.models.RunwayStaticSiteModuleParametersDataModel[source]
Bases:
runway.config.models.base.ConfigPropertyModel for Runway static site Module parameters.
- acmcert_arn
The certificate arn used for any alias domains supplied. This is a requirement when supplying any custom domain.
- Type
Optional[str]
- additional_redirect_domains
Additional domains (beyond the
aliasesdomains or the CloudFront URL if no aliases are provided) that will be authorized by the Auth@Edge UserPool AppClient.- Type
List[str]
- auth_at_edge
Auth@Edge make the static site private by placing it behind an authorization wall.
- Type
- compress
Whether the CloudFront default cache behavior will automatically compress certain files.
- Type
- cookie_settings
The default cookie settings for retrieved tokens and generated nonce’s.
- custom_error_responses
Define custom error responses.
- lambda_function_associations
This allows the user to deploy custom Lambda@Edge associations with their pre-build function versions.
- oauth_scopes
Scope is a mechanism in OAuth 2.0 to limit an application’s access to a user’s account.
- Type
List[str]
- redirect_path_auth_refresh
The path that a user is redirected to when their authorization tokens have expired (1 hour).
- Type
- required_group
Name of Cognito User Pool group of which users must be a member to be granted access to the site. If
None, allows all UserPool users to have access.- Type
Optional[str]
- rewrite_directory_index
Deploy a Lambda@Edge function designed to rewrite directory indexes.
- Type
Optional[str]
- role_boundary_arn
Defines an IAM Managed Policy that will be set as the permissions boundary for any IAM Roles created to support the site.
- Type
Optional[str]
- supported_identity_providers
A comma delimited list of the User Pool client identity providers.
- Type
List[str]
- user_pool_arn
The ARN of a pre-existing Cognito User Pool to use with Auth@Edge.
- Type
Optional[str]
- web_acl
The ARN of a web access control list (web ACL) to associate with the CloudFront Distribution.
- Type
Optional[str]
- class Config[source]
Bases:
runway.config.models.base.ConfigProperty.ConfigModel configuration.
- __init__()
- __new__(**kwargs)
- classmethod get_field_info(name: unicode) Dict[str, Any]
Get properties of FieldInfo from the fields property of the config class.
- getter_dict
alias of
pydantic.utils.GetterDict
- json_dumps(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Serialize
objto a JSON formattedstr.If
skipkeysis true thendictkeys that are not basic types (str,int,float,bool,None) will be skipped instead of raising aTypeError.If
ensure_asciiis false, then the return value can contain non-ASCII characters if they appear in strings contained inobj. Otherwise, all such characters are escaped in JSON strings.If
check_circularis false, then the circular reference check for container types will be skipped and a circular reference will result in anRecursionError(or worse).If
allow_nanis false, then it will be aValueErrorto serialize out of rangefloatvalues (nan,inf,-inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN,Infinity,-Infinity).If
indentis a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines.Noneis the most compact representation.If specified,
separatorsshould be an(item_separator, key_separator)tuple. The default is(', ', ': ')if indent isNoneand(',', ': ')otherwise. To get the most compact JSON representation, you should specify(',', ':')to eliminate whitespace.default(obj)is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.If sort_keys is true (default:
False), then the output of dictionaries will be sorted by key.To use a custom
JSONEncodersubclass (e.g. one that overrides the.default()method to serialize additional types), specify it with theclskwarg; otherwiseJSONEncoderis used.
- json_loads(*, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)
Deserialize
s(astr,bytesorbytearrayinstance containing a JSON document) to a Python object.object_hookis an optional function that will be called with the result of any object literal decode (adict). The return value ofobject_hookwill be used instead of thedict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).object_pairs_hookis an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value ofobject_pairs_hookwill be used instead of thedict. This feature can be used to implement custom decoders. Ifobject_hookis also defined, theobject_pairs_hooktakes priority.parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.To use a custom
JSONDecodersubclass, specify it with theclskwarg; otherwiseJSONDecoderis used.
- __contains__(name: object) bool
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- __setitem__(name: str, value: Any) None
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- get(name: str, default: Optional[Any] = None) Any
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
Static website Module.
- class runway.module.staticsite.handler.StaticSite[source]
Bases:
runway.module.base.RunwayModuleStatic website Runway Module.
- __init__(context: RunwayContext, *, explicitly_enabled: Optional[bool] = False, logger: RunwayLogger = <RunwayLogger runway.module.staticsite.handler (WARNING)>, module_root: Path, name: Optional[str] = None, options: Optional[Union[Dict[str, Any], ModuleOptions]] = None, parameters: Optional[Dict[str, Any]] = None, **_: Any) None[source]
Instantiate class.
- Parameters
context – Runway context object for the current session.
explicitly_enabled – Whether or not the module is explicitly enabled. This is can be set in the event that the current environment being deployed to matches the defined environments of the module/deployment.
logger – Used to write logs.
module_root – Root path of the module.
name – Name of the module.
options – Options passed to the module class from the config as
optionsormodule_optionsif coming from the deployment level.parameters – Values to pass to the underlying infrastructure as code tool that will alter the resulting infrastructure being deployed. Used to templatize IaC.
- property sanitized_name: str
Sanitized name safe to use in a CloudFormation Stack name.
Errors are usually caused here by a
.in the name. This unintelligently replaces.with-.If issues are still encountered, we can check against the regex of
(?=^.{1,128}$)^[a-zA-Z][-a-zA-Z0-9_]+$.
- __new__(**kwargs)
Static site utilities.
Base classes for runway modules.
- class runway.module.base.RunwayModule[source]
Bases:
objectBase class for Runway modules.
- __init__(context: RunwayContext, *, explicitly_enabled: Optional[bool] = False, logger: RunwayLogger = <RunwayLogger runway.module.base (WARNING)>, module_root: Path, name: Optional[str] = None, options: Optional[Union[Dict[str, Any], ModuleOptions]] = None, parameters: Optional[Dict[str, Any]] = None, **_: Any) None[source]
Instantiate class.
- Parameters
context – Runway context object for the current session.
explicitly_enabled – Whether or not the module is explicitly enabled. This is can be set in the event that the current environment being deployed to matches the defined environments of the module/deployment.
logger – Used to write logs.
module_root – Root path of the module.
name – Name of the module.
options – Options passed to the module class from the config as
optionsormodule_optionsif coming from the deployment level.parameters – Values to pass to the underlying infrastructure as code tool that will alter the resulting infrastructure being deployed. Used to templatize IaC.
- __getitem__(key: str) Any[source]
Make the object subscriptable.
- Parameters
key – Attribute to get.
- __new__(**kwargs)
- class runway.module.base.RunwayModuleNpm[source]
Bases:
runway.module.base.RunwayModuleBase class for Runway modules that use npm.
- __init__(context: RunwayContext, *, explicitly_enabled: Optional[bool] = False, logger: RunwayLogger = <RunwayLogger runway.module.base (WARNING)>, module_root: Path, name: Optional[str] = None, options: Optional[Union[Dict[str, Any], ModuleOptions]] = None, parameters: Optional[Dict[str, Any]] = None, **_: Any) None[source]
Instantiate class.
- Parameters
context – Runway context object for the current session.
explicitly_enabled – Whether or not the module is explicitly enabled. This is can be set in the event that the current environment being deployed to matches the defined environments of the module/deployment.
logger – Used to write logs.
module_root – Root path of the module.
name – Name of the module.
options – Options passed to the module class from the config as
optionsormodule_optionsif coming from the deployment level.parameters – Values to pass to the underlying infrastructure as code tool that will alter the resulting infrastructure being deployed. Used to templatize IaC.
- log_npm_command(command: List[str]) None[source]
Log an npm command that is going to be run.
- Parameters
command – List that will be passed into a subprocess.
- __new__(**kwargs)
- package_json_missing() bool[source]
Check for the existence for a package.json file in the module.
- Returns
True if the file was not found.
- Return type
- static check_for_npm(*, logger: Union[logging.Logger, PrefixAdaptor, RunwayLogger] = <RunwayLogger runway.module.base (WARNING)>) None[source]
Ensure npm is installed and in the current path.
- Parameters
logger – Optionally provide a custom logger to use.
- static warn_on_boto_env_vars(env_vars: Dict[str, str], *, logger: Union[logging.Logger, PrefixAdaptor, RunwayLogger] = <RunwayLogger runway.module.base (WARNING)>) None[source]
Inform user if boto-specific environment variables are in use.
- Parameters
env_vars – Environment variables to check.
logger – Optionally provide a custom logger to use.
CDK module.
- class runway.module.cdk.CloudDevelopmentKit[source]
Bases:
runway.module.base.RunwayModuleNpmCDK Runway Module.
- __init__(context: RunwayContext, *, explicitly_enabled: Optional[bool] = False, logger: RunwayLogger = <RunwayLogger runway.module.cdk (WARNING)>, module_root: Path, name: Optional[str] = None, options: Optional[Union[Dict[str, Any], ModuleOptions]] = None, parameters: Optional[Dict[str, Any]] = None, **_: Any) None[source]
Instantiate class.
- Parameters
context – Runway context object for the current session.
explicitly_enabled – Whether or not the module is explicitly enabled. This is can be set in the event that the current environment being deployed to matches the defined environments of the module/deployment.
logger – Used to write logs.
module_root – Root path of the module.
name – Name of the module.
options – Options passed to the module class from the config as
optionsormodule_optionsif coming from the deployment level.parameters – Values to pass to the underlying infrastructure as code tool that will alter the resulting infrastructure being deployed. Used to templatize IaC.
- property cli_args_context: List[str]
Generate CLI args from self passed to CDK commands as
--context.
- gen_cmd(command: typing_extensions.Literal[bootstrap, context, deploy, destroy, diff, docs, doctor, init, list, metadata, synthesize], args_list: Optional[List[str]] = None, *, include_context: bool = False) List[str][source]
Generate and log a CDK command.
This does not execute the command, only prepares it for use.
- Parameters
command – The CDK command to be executed.
args_list – Additional arguments to include in the generated command.
include_context – Optionally, pass context to the CLI. Context is not valid for all commands.
- Returns
The full command to be passed into a subprocess.
- __new__(**kwargs)
- static check_for_npm(*, logger: Union[logging.Logger, PrefixAdaptor, RunwayLogger] = <RunwayLogger runway.module.base (WARNING)>) None
Ensure npm is installed and in the current path.
- Parameters
logger – Optionally provide a custom logger to use.
- log_npm_command(command: List[str]) None
Log an npm command that is going to be run.
- Parameters
command – List that will be passed into a subprocess.
- package_json_missing() bool
Check for the existence for a package.json file in the module.
- Returns
True if the file was not found.
- Return type
- static warn_on_boto_env_vars(env_vars: Dict[str, str], *, logger: Union[logging.Logger, PrefixAdaptor, RunwayLogger] = <RunwayLogger runway.module.base (WARNING)>) None
Inform user if boto-specific environment variables are in use.
- Parameters
env_vars – Environment variables to check.
logger – Optionally provide a custom logger to use.
- class runway.module.cdk.CloudDevelopmentKitOptions[source]
Bases:
runway.module.base.ModuleOptionsModule options for AWS Cloud Development Kit.
- build_steps
A list of commands to be executed before each action (e.g. diff, deploy, destroy).
- data
Options parsed into a data model.
- skip_npm_ci
Skip running
npm ciin the module directory prior to processing the module.
- __init__(data: runway.config.models.runway.options.cdk.RunwayCdkModuleOptionsDataModel) None[source]
Instantiate class.
- Parameters
data – Options parsed into a data model.
- classmethod parse_obj(obj: object) runway.module.cdk.CloudDevelopmentKitOptions[source]
Parse options definition and return an options object.
- Parameters
obj – Object to parse.
- __new__(**kwargs)
Cloudformation module.
- class runway.module.cloudformation.CloudFormation[source]
Bases:
runway.module.base.RunwayModuleCloudFormation (CFNgin) Runway Module.
- __init__(context: RunwayContext, *, explicitly_enabled: Optional[bool] = False, logger: RunwayLogger = <RunwayLogger runway.module.cloudformation (WARNING)>, module_root: Path, name: Optional[str] = None, options: Optional[Union[Dict[str, Any], ModuleOptions]] = None, parameters: Optional[Dict[str, Any]] = None, **_: Any) None[source]
Instantiate class.
- Parameters
context – Runway context object for the current session.
explicitly_enabled – Whether or not the module is explicitly enabled. This is can be set in the event that the current environment being deployed to matches the defined environments of the module/deployment.
logger – Used to write logs.
module_root – Root path of the module.
name – Name of the module.
options – Options passed to the module class from the config as
optionsormodule_optionsif coming from the deployment level.parameters – Values to pass to the underlying infrastructure as code tool that will alter the resulting infrastructure being deployed. Used to templatize IaC.
- __new__(**kwargs)
K8s (kustomize) module.
- class runway.module.k8s.K8s[source]
Bases:
runway.module.base.RunwayModuleKubectl Runway Module.
- __init__(context: RunwayContext, *, explicitly_enabled: Optional[bool] = False, logger: RunwayLogger = <RunwayLogger runway.module.k8s (WARNING)>, module_root: Path, name: Optional[str] = None, options: Optional[Union[Dict[str, Any], ModuleOptions]] = None, parameters: Optional[Dict[str, Any]] = None, **_: Any) None[source]
Instantiate class.
- Parameters
context – Runway context object for the current session.
explicitly_enabled – Whether or not the module is explicitly enabled. This is can be set in the event that the current environment being deployed to matches the defined environments of the module/deployment.
logger – Used to write logs.
module_root – Root path of the module.
name – Name of the module.
options – Options passed to the module class from the config as
optionsormodule_optionsif coming from the deployment level.parameters – Values to pass to the underlying infrastructure as code tool that will alter the resulting infrastructure being deployed. Used to templatize IaC.
- property kbenv: runway.env_mgr.kbenv.KBEnvManager
Kubectl environment manager.
- gen_cmd(command: typing_extensions.Literal[annotation, apply, auth, autoscale, cp, create, delete, describe, diff, edit, exec, expose, get, kustomize, label, logs, patch, port - forward, proxy], args_list: Optional[List[str]] = None) List[str][source]
Generate and log a kubectl command.
This does not execute the command, only prepares it for use.
- Parameters
command – The CDK command to be executed.
args_list – Additional arguments to include in the generated command.
- Returns
The full command to be passed into a subprocess.
- kubectl_apply() None[source]
Execute
kubectl applycommand.https://kubectl.docs.kubernetes.io/references/kubectl/apply/
- kubectl_delete() None[source]
Execute
kubectl deletecommand.https://kubectl.docs.kubernetes.io/references/kubectl/delete/
- kubectl_kustomize() str[source]
Execute
kubectl kustomizecommand.https://kubectl.docs.kubernetes.io/references/kubectl/kustomize/
- __new__(**kwargs)
- class runway.module.k8s.K8sOptions[source]
Bases:
runway.module.base.ModuleOptionsModule options for Kubernetes.
- data
Options parsed into a data model.
- deploy_environment
Runway deploy environment object.
- path
Module path.
- Type
- __init__(data: runway.config.models.runway.options.k8s.RunwayK8sModuleOptionsDataModel, deploy_environment: runway.core.components._deploy_environment.DeployEnvironment, path: pathlib.Path) None[source]
Instantiate class.
- Parameters
data – Options parsed into a data model.
deploy_environment – Current deploy environment.
path – Module path.
- property kustomize_config: pathlib.Path
Kustomize configuration file.
- property overlay_path: pathlib.Path
Directory containing the kustomize overlay to use.
- __new__(**kwargs)
- static gen_overlay_dirs(environment: str, region: str) List[str][source]
Generate possible overlay directories.
Prefers more explicit directory name but falls back to environment name only.
- Parameters
environment – Current deploy environment.
region – Current AWS region.
- classmethod get_overlay_dir(path: pathlib.Path, environment: str, region: str) pathlib.Path[source]
Determine the overlay directory to use.
- classmethod parse_obj(deploy_environment: runway.core.components._deploy_environment.DeployEnvironment, obj: object, path: Optional[pathlib.Path] = None) runway.module.k8s.K8sOptions[source]
Parse options definition and return an options object.
- Parameters
deploy_environment – Current deploy environment.
obj – Object to parse.
path – Module path.
Serverless module.
- runway.module.serverless.gen_sls_config_files(stage: str, region: str) List[str][source]
Generate possible SLS config files names.
- class runway.module.serverless.Serverless[source]
Bases:
runway.module.base.RunwayModuleNpmServerless Runway Module.
- __init__(context: RunwayContext, *, explicitly_enabled: Optional[bool] = False, logger: RunwayLogger = <RunwayLogger runway.module.serverless (WARNING)>, module_root: Path, name: Optional[str] = None, options: Optional[Union[Dict[str, Any], ModuleOptions]] = None, parameters: Optional[Dict[str, Any]] = None, **_: Any) None[source]
Instantiate class.
- Parameters
context – Runway context object for the current session.
explicitly_enabled – Whether or not the module is explicitly enabled. This is can be set in the event that the current environment being deployed to matches the defined environments of the module/deployment.
logger – Used to write logs.
module_root – Root path of the module.
name – Name of the module.
options – Options passed to the module class from the config as
optionsormodule_optionsif coming from the deployment level.parameters – Values to pass to the underlying infrastructure as code tool that will alter the resulting infrastructure being deployed. Used to templatize IaC.
- property env_file: Optional[pathlib.Path]
Find the environment file for the module.
- extend_serverless_yml(func: Callable[[...], None]) None[source]
Extend the Serverless config file with additional YAML from options.
- Parameters
func – Callable to use after handling the Serverless config file.
- gen_cmd(command: str, args_list: Optional[List[str]] = None) List[str][source]
Generate and log a Serverless command.
This does not execute the command, only prepares it for use.
- Parameters
command – The Serverless command to be executed.
args_list – Additional arguments to include in the generated command.
- Returns
The full command to be passed into a subprocess.
- sls_deploy(*, package: Optional[AnyPath] = None, skip_install: bool = False) None[source]
Execute
sls deploycommand.- Parameters
package – Path to Serverless package to deploy.
skip_install – Skip
npm ci|installbefore running the Serverless command.
- sls_package(*, output_path: Optional[AnyPathConstrained] = None, skip_install: bool = False) Optional[AnyPathConstrained][source]
Execute
sls packagecommand.- Parameters
output_path – Path where the package should be output.
skip_install – Skip
npm ci|installbefore running the Serverless command.
- sls_print(*, item_path: Optional[str] = None, skip_install: bool = False) Dict[str, Any][source]
Execute
sls printcommand.- Keyword Arguments
item_path – Period-separated path to print a sub-value (eg: “provider.name”).
skip_install – Skip
npm ci|installbefore running the Serverless command.
- Returns
Resolved Serverless config file.
- Raises
SystemExit – If a runway-tmp.serverless.yml file already exists.
- sls_remove(*, skip_install: bool = False) None[source]
Execute
sls removecommand.- Parameters
skip_install – Skip
npm ci|installbefore running the Serverless command.
- __new__(**kwargs)
- static check_for_npm(*, logger: Union[logging.Logger, PrefixAdaptor, RunwayLogger] = <RunwayLogger runway.module.base (WARNING)>) None
Ensure npm is installed and in the current path.
- Parameters
logger – Optionally provide a custom logger to use.
- log_npm_command(command: List[str]) None
Log an npm command that is going to be run.
- Parameters
command – List that will be passed into a subprocess.
- package_json_missing() bool
Check for the existence for a package.json file in the module.
- Returns
True if the file was not found.
- Return type
- static warn_on_boto_env_vars(env_vars: Dict[str, str], *, logger: Union[logging.Logger, PrefixAdaptor, RunwayLogger] = <RunwayLogger runway.module.base (WARNING)>) None
Inform user if boto-specific environment variables are in use.
- Parameters
env_vars – Environment variables to check.
logger – Optionally provide a custom logger to use.
- class runway.module.serverless.ServerlessArtifact[source]
Bases:
objectObject for interacting with a Serverless artifact directory.
- __init__(context: RunwayContext, config: Dict[str, Any], *, logger: Union[PrefixAdaptor, RunwayLogger] = <RunwayLogger runway.module.serverless (WARNING)>, package_path: AnyPath, path: AnyPath) None[source]
Instantiate class.
- Parameters
context – Runway context object.
config – Rendered Serverless config file.
logger – Logger this object will log to. If not provided, the logger in the local module will be used.
package_path – Local path to the artifact directory.
path – Root directory of the Serverless project.
- sync_with_s3(bucket_name: str) None[source]
Sync local archive files with S3 bucket.
- Parameters
bucket_name – Name of S3 bucket to upload files to.
- __new__(**kwargs)
- class runway.module.serverless.ServerlessOptions[source]
Bases:
runway.module.base.ModuleOptionsModule options for Serverless Framework.
- data
Options parsed into a data model.
- extend_serverless_yml
If provided, the value of this option will be recursively merged into the module’s Serverless config file.
- promotezip
If provided, promote Serverless Framework generated zip files between environments from a build AWS account.
- skip_npm_ci
Skip running
npm ciin the module directory prior to processing the module.
- __init__(data: runway.config.models.runway.options.serverless.RunwayServerlessModuleOptionsDataModel) None[source]
Instantiate class.
- Parameters
data – Options parsed into a data model.
- update_args(key: str, value: str) None[source]
Update a known CLI argument.
- Parameters
key – Dict key to be updated.
value – New value
- Raises
KeyError – The key provided for update is not a known arg.
- classmethod parse_obj(obj: object) runway.module.serverless.ServerlessOptions[source]
Parse options definition and return an options object.
- Parameters
obj – Object to parse.
- __new__(**kwargs)
Terraform module.
- runway.module.terraform.gen_workspace_tfvars_files(environment: str, region: str) List[str][source]
Generate possible Terraform workspace tfvars filenames.
- runway.module.terraform.update_env_vars_with_tf_var_values(os_env_vars: Dict[str, str], tf_vars: Dict[str, Union[Dict[str, Any], List[Any], str]]) Dict[str, str][source]
Return os_env_vars with TF_VAR values for each tf_var.
- class runway.module.terraform.Terraform[source]
Bases:
runway.module.base.RunwayModule,runway.mixins.DelCachedPropMixinTerraform Runway Module.
- __init__(context: RunwayContext, *, explicitly_enabled: Optional[bool] = False, logger: RunwayLogger = <RunwayLogger runway.module.terraform (WARNING)>, module_root: Path, name: Optional[str] = None, options: Optional[Union[Dict[str, Any], ModuleOptions]] = None, parameters: Optional[Dict[str, Any]] = None, **_: Any) None[source]
Instantiate class.
- Parameters
context – Runway context object for the current session.
explicitly_enabled – Whether or not the module is explicitly enabled. This is can be set in the event that the current environment being deployed to matches the defined environments of the module/deployment.
logger – Used to write logs.
module_root – Root path of the module.
name – Name of the module.
options – Options passed to the module class from the config as
optionsormodule_optionsif coming from the deployment level.parameters – Values to pass to the underlying infrastructure as code tool that will alter the resulting infrastructure being deployed. Used to templatize IaC.
- property auto_tfvars: pathlib.Path
Return auto.tfvars file if one is being used.
- property current_workspace: str
Wrap “terraform_workspace_show” to cache the value.
- Returns
The currently active Terraform workspace.
- property tfenv: runway.env_mgr.tfenv.TFEnvManager
Terraform environment manager.
- property version: runway.utils._version.Version
Version of Terraform being used.
- cleanup_dot_terraform() None[source]
Remove .terraform excluding the plugins directly.
This step is crucial for allowing Runway to deploy to multiple regions or deploy environments without prompting the user for input.
The plugins directory is retained to improve performance when they are used by subsequent runs.
- gen_command(command: Union[List[str], str, Tuple[str, ...]], args_list: Optional[List[str]] = None) List[str][source]
Generate Terraform command.
- handle_backend() None[source]
Handle backend configuration.
This needs to be run before “skip” is assessed or env_file/auto_tfvars is used in case their behavior needs to be altered.
- handle_parameters() None[source]
Handle parameters.
Either updating environment variables or writing to a file.
- terraform_workspace_list() str[source]
Execute
terraform workspace listcommand.https://www.terraform.io/docs/cli/commands/workspace/list.html
- Returns
The available Terraform workspaces.
- Return type
- terraform_workspace_new(workspace: str) None[source]
Execute
terraform workspace newcommand.permanently to https://www.terraform.io/docs/cli/commands/workspace/new.html
- Parameters
workspace – Terraform workspace to create.
- terraform_workspace_select(workspace: str) None[source]
Execute
terraform workspace selectcommand.https://www.terraform.io/docs/cli/commands/workspace/select.html
- Parameters
workspace – Terraform workspace to select.
- terraform_workspace_show() str[source]
Execute
terraform workspace showcommand.https://www.terraform.io/docs/cli/commands/workspace/show.html
- Returns
The current Terraform workspace.
- run(action: typing_extensions.Literal[apply, destroy, get, init, plan, workspace_list, workspace_new, workspace_select, workspace_show]) None[source]
Run module.
- __new__(**kwargs)
- class runway.module.terraform.TerraformOptions[source]
Bases:
runway.module.base.ModuleOptionsModule options for Terraform.
- args
CLI arguments/options to pass to Terraform.
- data
Options parsed into a data model.
- env
Current deploy environment.
- path
Module path.
- version
String containing a Terraform version.
- write_auto_tfvars
Optionally write parameters to a tfvars file instead of updating variables.
- __init__(data: RunwayTerraformModuleOptionsDataModel, deploy_environment: DeployEnvironment, path: Optional[Path] = None) None[source]
Instantiate class.
- Parameters
deploy_environment – Current deploy environment.
data – Options parsed into a data model.
path – Module path.
- property backend_config: runway.module.terraform.TerraformBackendConfig
Backend configuration options.
- classmethod parse_obj(deploy_environment: DeployEnvironment, obj: object, path: Optional[Path] = None) TerraformOptions[source]
Parse options definition and return an options object.
- Parameters
deploy_environment – Current deploy environment.
obj – Object to parse.
path – Module path.
- __new__(**kwargs)
- class runway.module.terraform.TerraformBackendConfig[source]
Bases:
runway.module.base.ModuleOptionsTerraform backend configuration module options.
- __init__(data: RunwayTerraformBackendConfigDataModel, deploy_environment: DeployEnvironment, path: Path) None[source]
Instantiate class.
- Parameters
data – Options parsed into a data model.
deploy_environment – Current deploy environment.
path – Module path.
- property config_file: Optional[pathlib.Path]
Backend configuration file.
- classmethod get_backend_file(path: pathlib.Path, environment: str, region: str) Optional[pathlib.Path][source]
Determine Terraform backend file.
- Parameters
path – Path to the module.
environment – Current deploy environment.
region – Current AWS region.
- static gen_backend_filenames(environment: str, region: str) List[str][source]
Generate possible Terraform backend filenames.
- Parameters
environment – Current deploy environment.
region – Current AWS region.
- classmethod parse_obj(deploy_environment: DeployEnvironment, obj: object, path: Optional[Path] = None) TerraformBackendConfig[source]
Parse options definition and return an options object.
- Parameters
deploy_environment – Current deploy environment.
obj – Object to parse.
path – Module path.
- __new__(**kwargs)
Runway module utilities.
- runway.module.utils.format_npm_command_for_logging(command: List[str]) str[source]
Convert npm command list to string for display to user.
- runway.module.utils.generate_node_command(command: str, command_opts: List[str], path: Path, *, logger: Union[logging.Logger, 'logging.LoggerAdapter[Any]'] = <RunwayLogger runway.module.utils (WARNING)>, package: Optional[str] = None) List[str][source]
Return node bin command list for subprocess execution.
- Parameters
command – Command to execute from a local
node_modules/.bin.command_opts – Options to include with the command.
path – Current working directory. Used to construct a “fall-back” command when
npxis not available/included as part of npm.logger – A specific logger to use when logging the constructed command.
package – Name of the npm package containing the binary to execute. This is recommended when the name of the binary does not match the name of the npm package.
- runway.module.utils.run_module_command(cmd_list: List[str], env_vars: Dict[str, str], exit_on_error: bool = True, logger: Union[logging.Logger, 'logging.LoggerAdapter[Any]'] = <RunwayLogger runway.module.utils (WARNING)>) None[source]
Shell out to provisioner command.
- Parameters
cmd_list – Command to run.
env_vars – Environment variables.
exit_on_error – If true,
subprocess.CalledProcessErrorwill be caught and the resulting exit code will be passed tosys.exit(). If false, the error will not be caught within this function. logger: Optionally, supply a logger to use.logger – A specific logger to use when logging the constructed command.
- runway.module.utils.use_npm_ci(path: pathlib.Path) bool[source]
Return true if npm ci should be used in lieu of npm install.
Empty init for python import traversal.
‘Git type Path Source.
- class runway.sources.git.Git[source]
Bases:
runway.sources.source.SourceGit Path Source.
The Git path source can be tasked with cloning a remote repository and pointing to a specific module folder (or the root).
- __init__(*, arguments: Optional[Dict[str, str]] = None, location: str = '', uri: str = '', **kwargs: Any) None[source]
Git Path Source.
- Parameters
arguments – A reference can be passed along via the arguments so that a specific version of the repository is cloned. commit, tag, branch are all valid keys with respective output
location – The relative location to the root of the repository where the module resides. Leaving this as an empty string,
/, or./will have runway look in the root folder.uri – The uniform resource identifier that targets the remote git repository
- fetch() pathlib.Path[source]
Retrieve the git repository from it’s remote location.
- classmethod sanitize_git_path(path: str) str[source]
Sanitize the git path for folder/file assignment.
- Keyword Arguments
path – The path string to be sanitized
- __new__(**kwargs)
Abstract parent class for a ‘Source’ type object.
Allows us to specify specific remote sourced resources for out application (Git, S3, ect.)
- class runway.sources.source.Source[source]
Bases:
objectAbstract parent class for a ‘Source’ type object.
The Source parent class allows us to specify remote resources for our application via services such as Git or S3. A cache directory, as part of object’s configuration, is automatically created by default:
./.runway/cache. This folder can be overridden by specifying thecache_dirproperty in the configuration passed.Every Source type object is expected to have a
fetchmethod which will return the folder path at where the module requested resides.- __init__(*, cache_dir: Union[pathlib.Path, str], **_: Any)[source]
Source.
- Parameters
cache_dir – The directory where the given remote resource should be cached.
- fetch() pathlib.Path[source]
Retrieve remote source. To be implemented in each subclass.
- __new__(**kwargs)
Empty init for python import traversal.
Import classes.
Base module for test handlers.
cfn-list test runner.
- class runway.tests.handlers.cfn_lint.CfnLintHandler[source]
Bases:
runway.tests.handlers.base.TestHandlerLints CFN.
- classmethod handle(name: str, args: Union[ConfigProperty, Dict[str, Any]]) None[source]
Perform the actual test.
Relies on .cfnlintrc file to be located beside the Runway config file.
- __init__()
- __new__(**kwargs)
Script test runner.
- class runway.tests.handlers.script.ScriptHandler[source]
Bases:
runway.tests.handlers.base.TestHandlerHandle script tests.
- Parameters
commands (List[str]) – A list of commands to be executed in order. Each command is run in its own subprocess. The working directory will be the same as where the ‘runway test’ command was executed.
Example
- classmethod handle(name: str, args: Union[ConfigProperty, Dict[str, Any]]) None[source]
Perform the actual test.
- __init__()
- __new__(**kwargs)
yamllint test runner.
Utility functions.
- class runway.utils.BaseModel[source]
Bases:
pydantic.main.BaseModelBase class for Runway models.
- get(name: str, default: Optional[Any] = None) Any[source]
Safely get the value of an attribute.
- Parameters
name – Attribute name to return the value for.
default – Value to return if attribute is not found.
- __contains__(name: object) bool[source]
Implement evaluation of ‘in’ conditional.
- Parameters
name – The name to check for existence in the model.
- __getitem__(name: str) Any[source]
Implement evaluation of self[name].
- Parameters
name – Attribute name to return the value for.
- Returns
The value associated with the provided name/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
- __setitem__(name: str, value: Any) None[source]
Implement item assignment (e.g.
self[name] = value).- Parameters
name – Attribute name to set.
value – Value to assign to the attribute.
- __init__(**data: Any) None
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- __iter__() TupleGenerator
so dict(model) works
- __new__(**kwargs)
- __pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
- __repr_name__() unicode
Name of the instance’s class, used in __repr__.
- __rich_repr__() RichReprResult
Get fields for Rich library
- classmethod __try_update_forward_refs__(**localns: Any) None
Same as update_forward_refs but will not raise exception when forward references are not defined.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- class runway.utils.JsonEncoder[source]
Bases:
json.encoder.JSONEncoderEncode Python objects to JSON data.
This class can be used with
json.dumps()to handle most data types that can occur in responses from AWS.- Usage:
>>> json.dumps(data, cls=JsonEncoder)
- default(o: Any) Any[source]
Encode types not supported by the default JSONEncoder.
- Parameters
o – Object to encode.
- Returns
JSON serializable data type.
- Raises
TypeError – Object type could not be encoded.
- __init__(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, sort_keys=False, indent=None, separators=None, default=None)
Constructor for JSONEncoder, with sensible defaults.
If skipkeys is false, then it is a TypeError to attempt encoding of keys that are not str, int, float or None. If skipkeys is True, such items are simply skipped.
If ensure_ascii is true, the output is guaranteed to be str objects with all incoming non-ASCII characters escaped. If ensure_ascii is false, the output can contain non-ASCII characters.
If check_circular is true, then lists, dicts, and custom encoded objects will be checked for circular references during encoding to prevent an infinite recursion (which would cause an RecursionError). Otherwise, no such check takes place.
If allow_nan is true, then NaN, Infinity, and -Infinity will be encoded as such. This behavior is not JSON specification compliant, but is consistent with most JavaScript based encoders and decoders. Otherwise, it will be a ValueError to encode such floats.
If sort_keys is true, then the output of dictionaries will be sorted by key; this is useful for regression tests to ensure that JSON serializations can be compared on a day-to-day basis.
If indent is a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines. None is the most compact representation.
If specified, separators should be an (item_separator, key_separator) tuple. The default is (’, ‘, ‘: ‘) if indent is
Noneand (‘,’, ‘: ‘) otherwise. To get the most compact JSON representation, you should specify (‘,’, ‘:’) to eliminate whitespace.If specified, default is a function that gets called for objects that can’t otherwise be serialized. It should return a JSON encodable version of the object or raise a
TypeError.
- __new__(**kwargs)
- encode(o)
Return a JSON string representation of a Python data structure.
>>> from json.encoder import JSONEncoder >>> JSONEncoder().encode({"foo": ["bar", "baz"]}) '{"foo": ["bar", "baz"]}'
- iterencode(o, _one_shot=False)
Encode the given object and yield each string representation as available.
For example:
for chunk in JSONEncoder().iterencode(bigobject): mysocket.write(chunk)
- class runway.utils.MutableMap[source]
Bases:
MutableMapping[str,Any]Base class for mutable map objects.
- __init__(**kwargs: Any) None[source]
Initialize class.
Provided
kwargsare added to the object as attributes.Example
- find(query: str, default: Optional[Any] = None, ignore_cache: bool = False) Any[source]
Find a value in the map.
Previously found queries are cached to increase search speed. The cached value should only be used if values are not expected to change.
- Parameters
query – A period delimited string that is split to search for nested values
default – The value to return if the query was unsuccessful.
ignore_cache – Ignore cached value.
- get(key: str, default: Optional[Any] = None) Any[source]
Implement evaluation of self.get.
- Parameters
key – Attribute name to return the value for.
default – Value to return if attribute is not found.
- __getitem__(key: str) Any[source]
Implement evaluation of self[key].
- Parameters
key – Attribute name to return the value for.
- Returns
The value associated with the provided key/attribute name.
- Raises
AttributeError – If attribute does not exist on this object.
Example
- __setitem__(key: str, value: Any) None[source]
Implement assignment to self[key].
- Parameters
key – Attribute name to associate with a value.
value – Value of a key/attribute.
Example
- __delitem__(key: str) None[source]
Implement deletion of self[key].
- Parameters
key – Attribute name to remove from the object.
Example
- __iter__() Iterator[Any][source]
Return iterator object that can iterate over all attributes.
Example
- __new__(**kwargs)
- clear() None. Remove all items from D.
- items() a set-like object providing a view on D's items
- keys() a set-like object providing a view on D's keys
- pop(k[, d]) v, remove specified key and return the corresponding value.
If key is not found, d is returned if given, otherwise KeyError is raised.
- popitem() (k, v), remove and return some (key, value) pair
as a 2-tuple; but raise KeyError if D is empty.
- setdefault(k[, d]) D.get(k,d), also set D[k]=d if k not in D
- update([E, ]**F) None. Update D from mapping/iterable E and F.
If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v
- values() an object providing a view on D's values
- class runway.utils.SafeHaven[source]
Bases:
ContextManager[SafeHaven]Context manager that caches and resets important values on exit.
Caches and resets os.environ, sys.argv, sys.modules, and sys.path.
- __init__(argv: Optional[Iterable[str]] = None, environ: Optional[Dict[str, str]] = None, sys_modules_exclude: Optional[Iterable[str]] = None, sys_path: Optional[Iterable[str]] = None) None[source]
Instantiate class.
- Parameters
argv – Override the value of sys.argv.
environ – Update os.environ.
sys_modules_exclude – A list of modules to exclude when reverting sys.modules to its previous state. These are checked as
module.startswith(name).sys_path – Override the value of sys.path.
- __enter__() runway.utils.SafeHaven[source]
Enter the context manager.
- Returns
Instance of the context manager.
- Return type
- __exit__(exc_type: Optional[Type[BaseException]], exc_value: Optional[BaseException], traceback: Optional[types.TracebackType]) None[source]
Exit the context manager.
- __new__(**kwargs)
- class runway.utils.YamlDumper[source]
Bases:
yaml.dumper.DumperCustom YAML Dumper.
This Dumper allows for YAML to be output to follow YAML spec 1.2, example 2.3 of collections (2.1). This provides an output that is more humanreadable and complies with yamllint.
Example
>>> print(yaml.dump({'key': ['val1', 'val2']}, Dumper=YamlDumper))
Note
YAML 1.2 Specification: https://yaml.org/spec/1.2/spec.html used for reference.
- __init__(stream, default_style=None, default_flow_style=False, canonical=None, indent=None, width=None, allow_unicode=None, line_break=None, encoding=None, explicit_start=None, explicit_end=None, version=None, tags=None, sort_keys=True)
- __new__(**kwargs)
- runway.utils.argv(*args: str) Iterator[None][source]
Context manager for temporarily changing sys.argv.
- runway.utils.change_dir(newdir: Union[pathlib.Path, str]) Iterator[None][source]
Change directory.
Adapted from http://stackoverflow.com/a/24176022
- Parameters
newdir – Path to change directory into.
- runway.utils.ensure_file_is_executable(path: str) None[source]
Exit if file is not executable.
- Parameters
path – Path to file.
- Raises
SystemExit – file is not executable.
- runway.utils.environ(env: Optional[Dict[str, str]] = None, **kwargs: str) Iterator[None][source]
Context manager for temporarily changing os.environ.
The original value of os.environ is restored upon exit.
- Parameters
env – Dictionary to use when updating os.environ.
- runway.utils.json_serial(obj: Any) Any[source]
JSON serializer for objects not serializable by default json code.
- runway.utils.load_object_from_string(fqcn: str, try_reload: bool = False) Union[type, Callable[[...], Any]][source]
Convert “.” delimited strings to a python object.
- Parameters
fqcn – A “.” delimited string representing the full path to an object (function, class, variable) inside a module
try_reload – Try to reload the module so any global variables set within the file during import are reloaded. This only applies to modules that are already imported and are not builtin.
- Returns
Object being imported from the provided path.
Example:
load_object_from_string("os.path.basename") load_object_from_string("logging.Logger") load_object_from_string("LocalClassName")
- runway.utils.merge_dicts(dict1: Dict[Any, Any], dict2: Dict[Any, Any], deep_merge: bool = True) Dict[str, Any][source]
- runway.utils.merge_dicts(dict1: List[Any], dict2: List[Any], deep_merge: bool = True) List[Any]
Merge dict2 into dict1.
- runway.utils.snake_case_to_kebab_case(value: str) str[source]
Convert snake_case to kebab-case.
- Parameters
value – The string value to convert.
- runway.utils.extract_boto_args_from_env(env_vars: Dict[str, str]) Dict[str, str][source]
Return boto3 client args dict with environment creds.
- runway.utils.flatten_path_lists(env_dict: Dict[str, Any], env_root: Optional[str] = None) Dict[str, Any][source]
Join paths in environment dict down to strings.
- runway.utils.merge_nested_environment_dicts(env_dicts: Dict[str, Any], env_name: Optional[str] = None, env_root: Optional[str] = None) Dict[str, Any][source]
Return single-level dictionary from dictionary of dictionaries.
- runway.utils.find_cfn_output(key: str, outputs: List[OutputTypeDef]) Optional[str][source]
Return CFN output value.
- Parameters
key – Name of the output.
outputs – List of Stack outputs.
- runway.utils.get_hash_for_filename(filename: str, hashfile_path: str) str[source]
Return hash for filename in the hashfile.
- runway.utils.ignore_exit_code_0() Iterator[None][source]
Capture exit calls and ignore those with exit code 0.
- runway.utils.fix_windows_command_list(commands: List[str]) List[str][source]
Return command list with working Windows commands.
npm on windows is npm.cmd, which will blow up subprocess.check_call([‘npm’, ‘…’])
Similar issues arise when calling python apps that will have a windows-only suffix applied to them.
- runway.utils.run_commands(commands: List[Union[str, List[str], Dict[str, Union[str, List[str]]]]], directory: Union[pathlib.Path, str], env: Optional[Dict[str, str]] = None) None[source]
Run list of commands.
- runway.utils.get_file_hash(filename: str, algorithm: typing_extensions.Literal[blake2b, md5, sha1, sha224, sha256, sha3_224, sha3_256, sha3_384, sha3_512, sha384, sha512, shake_128, shake_256]) str[source]
Return cryptographic hash of file.
Deprecated since version 2.4.0: Use
runway.utils.FileHashinstead.
- runway.utils.md5sum(filename: str) str[source]
Return MD5 hash of file.
Deprecated since version 2.4.0: Use
runway.utils.FileHashinstead.
- runway.utils.sha256sum(filename: str) str[source]
Return SHA256 hash of file.
Deprecated since version 2.4.0: Use
runway.utils.FileHashinstead.
Submodules
Python dependency compatibility handling.
- exception runway.compat.PackageNotFoundError[source]
Bases:
ModuleNotFoundErrorThe package was not found.
- __init__(*args, **kwargs)
- __new__(**kwargs)
- msg
exception message
- name
module name
- path
module path
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- runway.compat.shlex_join(split_command)
Return a shell-escaped string from split_command.
Runway constants.
- runway.constants.BOTO3_CREDENTIAL_CACHE: Dict[str, Any] = {}
A global credential cache that can be shared among boto3 sessions. This is inherently threadsafe thanks to the GIL. (https://docs.python.org/3/glossary.html#term-global-interpreter-lock)
Runway exceptions.
- exception runway.exceptions.RunwayError[source]
Bases:
ExceptionBase class for custom exceptions raised by Runway.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.exceptions.ConfigNotFound[source]
Bases:
runway.exceptions.RunwayErrorConfiguration file could not be found.
- __init__(*, looking_for: Optional[List[str]] = None, path: pathlib.Path) None[source]
Instantiate class.
- Parameters
path – Path where the config file was expected to be found.
looking_for – List of file names that were being looked for.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.exceptions.DockerConnectionRefusedError[source]
Bases:
runway.exceptions.RunwayErrorDocker connection refused.
This can be caused by a number of reasons:
Docker is not installed.
Docker service is not running.
The current user does not have adequate permissions (e.g. not a member of the
dockergroup).
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.exceptions.DockerExecFailedError[source]
Bases:
runway.exceptions.RunwayErrorDocker failed when trying to execute a command.
This can be used for
docker container run,docker container startanddocker execequivalents.- __init__(response: Dict[str, Any]) None[source]
Instantiate class.
- Parameters
response – The return value of
docker.models.containers.Container.wait(), Docker API’s response as a Python dictionary. This can contain important log information pertinent to troubleshooting that may not streamed.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.exceptions.FailedLookup[source]
Bases:
runway.exceptions.RunwayErrorIntermediary Exception to be converted to FailedVariableLookup.
Should be caught by error handling and
runway.cfngin.exceptions.FailedVariableLookupraised instead to construct a proper error message.- __init__(lookup: VariableValueLookup, cause: Exception, *args: Any, **kwargs: Any) None[source]
Instantiate class.
- Parameters
lookup – The variable value lookup that was attempted and resulted in an exception being raised.
cause – The exception that was raised.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.exceptions.FailedVariableLookup[source]
Bases:
runway.exceptions.RunwayErrorLookup could not be resolved.
Raised when an exception is raised when trying to resolve a lookup.
- __init__(variable: Variable, lookup_error: FailedLookup, *args: Any, **kwargs: Any) None[source]
Instantiate class.
- Parameters
variable – The variable containing the failed lookup.
lookup_error – The exception that was raised directly before this one.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.exceptions.HclParserError[source]
Bases:
runway.exceptions.RunwayErrorHCL/HCL2 parser error.
- __init__(exc: Exception, file_path: Union[Path, str], parser: Optional[ModuleType] = None) None[source]
Instantiate class.
- Parameters
exc – Exception that was raised.
file_path – File that resulted in the error.
parser – The parser what was used to try to parse the file (hcl|hcl2).
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.exceptions.InvalidLookupConcatenation[source]
Bases:
runway.exceptions.RunwayErrorInvalid return value for a concatenated (chained) lookup.
The return value must be a string when lookups are concatenated.
- __init__(invalid_lookup: VariableValue, concat_lookups: VariableValueConcatenation[Any], *args: Any, **kwargs: Any) None[source]
Instantiate class.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.exceptions.KubectlVersionNotSpecified[source]
Bases:
runway.exceptions.RunwayErrorkubectl version is required but was not specified.
Version can be specified by using a file or option.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.exceptions.NpmNotFound[source]
Bases:
runway.exceptions.RunwayErrorRaised when npm could not be executed or was not found in path.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.exceptions.OutputDoesNotExist[source]
Bases:
runway.exceptions.RunwayErrorRaised when a specific stack output does not exist.
- __init__(stack_name: str, output: str, *args: Any, **kwargs: Any) None[source]
Instantiate class.
- Parameters
stack_name – Name of the stack.
output – The output that does not exist.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.exceptions.RequiredTagNotFoundError[source]
Bases:
runway.exceptions.RunwayErrorRequired tag not found on resource.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.exceptions.UnknownLookupType[source]
Bases:
runway.exceptions.RunwayErrorLookup type provided does not match a registered lookup.
Example
If a lookup of
${<lookup_type> query}is used and<lookup_type>is not a registered lookup, this exception will be raised.- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- __init__(lookup: VariableValueLookup, *args: Any, **kwargs: Any) None[source]
Instantiate class.
- Parameters
lookup – Variable value lookup that could not find a handler.
- exception runway.exceptions.UnresolvedVariable[source]
Bases:
runway.exceptions.RunwayErrorRaised when trying to use a variable before it has been resolved.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- exception runway.exceptions.UnresolvedVariableValue[source]
Bases:
runway.exceptions.RunwayErrorIntermediary Exception to be converted to UnresolvedVariable.
Should be caught by error handling and
runway.cfngin.exceptions.UnresolvedVariableraised instead to construct a proper error message.- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- __init__(lookup: VariableValueLookup, *args: Any, **kwargs: Any) None[source]
Instantiate class.
- Parameters
lookup – The variable value lookup that is not resolved.
- exception runway.exceptions.VariablesFileNotFound[source]
Bases:
runway.exceptions.RunwayErrorDefined variables file could not be found.
- __new__(**kwargs)
- with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
- __init__(file_path: pathlib.Path) None[source]
Instantiate class.
- Parameters
file_path – Path where the file was expected to be found.
Class mixins.
- class runway.mixins.CliInterfaceMixin[source]
Bases:
objectMixin for adding CLI interface methods.
- ctx: Union[CfnginContext, RunwayContext]
CFNgin or Runway context object.
- cwd: Path
Working directory where commands will be run.
- static convert_to_cli_arg(arg_name: str, *, prefix: str = '--') str[source]
Convert string kwarg name into a CLI argument.
- classmethod generate_command(command: Union[List[str], str], **kwargs: Optional[Union[bool, Iterable[str], str]]) List[str][source]
Generate command to be executed and log it.
- Parameters
command – Command to run.
args – Additional args to pass to the command.
- Returns
The full command to be passed into a subprocess.
- static list2cmdline(split_command: Iterable[str]) str[source]
Combine a list of strings into a string that can be run as a command.
Handles multi-platform differences.
- __init__()
- __new__(**kwargs)
Utility functions for S3.
- runway.s3_utils.purge_and_delete_bucket(bucket_name: str, region: str = 'us-east-1', session: Optional[boto3.session.Session] = None) None[source]
Delete all objects and versions in bucket, then delete bucket.
- runway.s3_utils.purge_bucket(bucket_name: str, region: str = 'us-east-1', session: Optional[boto3.session.Session] = None) None[source]
Delete all objects and versions in bucket.
- runway.s3_utils.delete_bucket(bucket_name: str, region: str = 'us-east-1', session: Optional[boto3.session.Session] = None) None[source]
Delete bucket.
- runway.s3_utils.does_bucket_exist(bucket_name: str, region: str = 'us-east-1', session: Optional[boto3.session.Session] = None) bool[source]
Check if bucket exists in S3.
- runway.s3_utils.ensure_bucket_exists(bucket_name: str, region: str = 'us-east-1', session: Optional[boto3.session.Session] = None) None[source]
Ensure S3 bucket exists.
- runway.s3_utils.does_s3_object_exist(bucket: str, key: str, session: Optional[boto3.session.Session] = None, region: str = 'us-east-1') bool[source]
Determine if object exists on s3.
- runway.s3_utils.upload(bucket: str, key: str, filename: str, session: Optional[boto3.session.Session] = None) None[source]
Upload file to S3 bucket.
- runway.s3_utils.download(bucket: str, key: str, file_path: str, session: Optional[boto3.session.Session] = None) str[source]
Download a file from S3 to the given path.
- runway.s3_utils.download_and_extract_to_mkdtemp(bucket: str, key: str, session: Optional[boto3.session.Session] = None) str[source]
Download zip archive and extract it to temporary directory.
- runway.s3_utils.get_matching_s3_objects(bucket: str, prefix: Sequence[str] = '', suffix: str = '', session: Optional[boto3.Session] = None) Iterator[ObjectTypeDef][source]
Generate objects in an S3 bucket.
- Parameters
bucket – Name of the S3 bucket.
prefix – Only fetch objects whose key starts with this prefix (optional).
suffix – Only fetch objects whose keys end with this suffix (optional).
session – Boto3/botocore session.
- runway.s3_utils.get_matching_s3_keys(bucket: str, prefix: str = '', suffix: str = '', session: Optional[boto3.session.Session] = None) Iterator[str][source]
Generate the keys in an S3 bucket.
- Parameters
bucket – Name of the S3 bucket.
prefix – Only fetch keys that start with this prefix (optional).
suffix – Only fetch keys that end with this suffix (optional).
session – Boto3/botocore session.
Type definitions.
Runway variables.
- class runway.variables.Variable[source]
Bases:
objectRepresents a variable provided to a Runway directive.
- __init__(name: str, value: Any, variable_type: typing_extensions.Literal[cfngin, runway] = 'cfngin') None[source]
Initialize class.
- Parameters
name – Name of the variable (directive/key).
value – The variable itself.
variable_type – Type of variable (cfngin|runway).
- property dependencies: Set[str]
Stack names that this variable depends on.
- Returns
Stack names that this variable depends on.
- Return type
Set[str]
- property resolved: bool
Boolean for whether the Variable has been resolved.
Variables only need to be resolved if they contain lookups.
- property value: Any
Return the current value of the Variable.
- Raises
UnresolvedVariable – Value accessed before it have been resolved.
- resolve(context: Union[CfnginContext, RunwayContext], provider: Optional[Provider] = None, variables: Optional[RunwayVariablesDefinition] = None, **kwargs: Any) None[source]
Resolve the variable value.
- Parameters
context – The current context object.
provider – Subclass of the base provider.
variables – Object containing variables passed to Runway.
- Raises
- get(key: str, default: Optional[Any] = None) Any[source]
Implement evaluation of self.get.
- Parameters
key – Attribute name to return the value for.
default – Value to return if attribute is not found.
- __new__(**kwargs)
- runway.variables.resolve_variables(variables: List[Variable], context: Union[CfnginContext, RunwayContext], provider: Optional[Provider] = None) None[source]
Given a list of variables, resolve all of them.
- Parameters
variables – List of variables.
context – CFNgin context.
provider – Subclass of the base provider.
- class runway.variables.VariableValue[source]
Bases:
objectSyntax tree base class to parse variable values.
- property dependencies: Set[Any]
Stack names that this variable depends on.
- property resolved: bool
Use to check if the variable value has been resolved.
- Raises
NotImplementedError – Should be defined in a subclass.
- property simplified: Any
Return a simplified version of the value.
This can be used to concatenate two literals into one literal or flatten nested concatenations.
Should be implimented in subclasses where applicable.
- property value: Any
Value of the variable. Can be resolved or unresolved.
- Raises
NotImplementedError – Should be defined in a subclass.
- resolve(context: Union[CfnginContext, RunwayContext], provider: Optional[Provider] = None, variables: Optional[RunwayVariablesDefinition] = None, **kwargs: Any) None[source]
Resolve the variable value.
- Parameters
context – The current context object.
provider – Subclass of the base provider.
variables – Object containing variables passed to Runway.
- classmethod parse_obj(obj: runway.variables._PydanticModelTypeVar, variable_type: typing_extensions.Literal[cfngin, runway] = 'cfngin') runway.variables.VariableValuePydanticModel[runway.variables._PydanticModelTypeVar][source]
- classmethod parse_obj(obj: Dict[str, Any], variable_type: typing_extensions.Literal[cfngin, runway] = 'cfngin') runway.variables.VariableValue
- classmethod parse_obj(obj: List[Any], variable_type: typing_extensions.Literal[cfngin, runway] = 'cfngin') runway.variables.VariableValueList
- classmethod parse_obj(obj: int, variable_type: typing_extensions.Literal[cfngin, runway] = 'cfngin') runway.variables.VariableValueLiteral[int]
- classmethod parse_obj(obj: str, variable_type: typing_extensions.Literal[cfngin, runway] = 'cfngin') runway.variables.VariableValueConcatenation[Union[runway.variables.VariableValueLiteral[str], runway.variables.VariableValueLookup]]
Parse complex variable structures using type appropriate subclasses.
- Parameters
obj – The objected defined as the value of a variable.
variable_type – Type of variable (cfngin|runway).
- __iter__() Iterator[Any][source]
How the object is iterated.
- Raises
NotImplementedError – Should be defined in a subclass.
- __repr__() str[source]
Return object representation.
- Raises
NotImplementedError – Should be defined in a subclass.
- __init__()
- __new__(**kwargs)
- class runway.variables.VariableValueDict[source]
Bases:
runway.variables.VariableValue,MutableMapping[str,runway.variables.VariableValue]A dict variable value.
- __init__(data: Dict[str, Any], variable_type: typing_extensions.Literal[cfngin, runway] = 'cfngin') None[source]
Instantiate class.
- Parameters
data – Data to be stored in the object.
variable_type – Type of variable (cfngin|runway).
- property simplified: Dict[str, Any]
Return a simplified version of the value.
This can be used to concatenate two literals into one literal or flatten nested concatenations.
- resolve(context: Union[CfnginContext, RunwayContext], provider: Optional[Provider] = None, variables: Optional[RunwayVariablesDefinition] = None, **kwargs: Any) None[source]
Resolve the variable value.
- Parameters
context – The current context object.
provider – Subclass of the base provider.
variables – Object containing variables passed to Runway.
- __getitem__(_VariableValueDict__key: str) runway.variables.VariableValue[source]
Get item by index.
- __setitem__(_VariableValueDict__key: str, _VariableValueDict__value: runway.variables.VariableValue) None[source]
Set item by index.
- __new__(**kwargs)
- clear() None. Remove all items from D.
- get(k[, d]) D[k] if k in D, else d. d defaults to None.
- items() a set-like object providing a view on D's items
- keys() a set-like object providing a view on D's keys
- classmethod parse_obj(obj: Any, variable_type: typing_extensions.Literal[cfngin, runway] = 'cfngin') runway.variables.VariableValue
Parse complex variable structures using type appropriate subclasses.
- Parameters
obj – The objected defined as the value of a variable.
variable_type – Type of variable (cfngin|runway).
- pop(k[, d]) v, remove specified key and return the corresponding value.
If key is not found, d is returned if given, otherwise KeyError is raised.
- popitem() (k, v), remove and return some (key, value) pair
as a 2-tuple; but raise KeyError if D is empty.
- setdefault(k[, d]) D.get(k,d), also set D[k]=d if k not in D
- update([E, ]**F) None. Update D from mapping/iterable E and F.
If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v
- values() an object providing a view on D's values
- class runway.variables.VariableValueList[source]
Bases:
runway.variables.VariableValue,MutableSequence[runway.variables.VariableValue]List variable value.
- __init__(iterable: Iterable[Any], variable_type: typing_extensions.Literal[cfngin, runway] = 'cfngin') None[source]
Instantiate class.
- Parameters
iterable – Data to store in the iterable.
variable_type – Type of variable (cfngin|runway).
- property simplified: List[runway.variables.VariableValue]
Return a simplified version of the value.
This can be used to concatenate two literals into one literal or flatten nested concatenations.
- property value: List[Any]
Value of the variable. Can be resolved or unresolved.
- insert(index: int, value: runway.variables.VariableValue) None[source]
Insert a value at a specific index.
- resolve(context: Union[CfnginContext, RunwayContext], provider: Optional[Provider] = None, variables: Optional[RunwayVariablesDefinition] = None, **kwargs: Any) None[source]
Resolve the variable value.
- Parameters
context – The current context object.
provider – Subclass of the base provider.
variables – Object containing variables passed to Runway.
- __getitem__(__index: int) runway.variables.VariableValue[source]
- __getitem__(__index: slice) List[runway.variables.VariableValue]
Get item by index.
- __setitem__(__index: int, __value: runway.variables.VariableValue) None[source]
- __setitem__(__index: slice, __value: List[runway.variables.VariableValue]) None
Set item by index.
- __iter__() Iterator[runway.variables.VariableValue][source]
Object iteration.
- __new__(**kwargs)
- append(value)
S.append(value) – append value to the end of the sequence
- clear() None -- remove all items from S
- count(value) integer -- return number of occurrences of value
- extend(values)
S.extend(iterable) – extend sequence by appending elements from the iterable
- index(value[, start[, stop]]) integer -- return first index of value.
Raises ValueError if the value is not present.
Supporting start and stop arguments is optional, but recommended.
- classmethod parse_obj(obj: Any, variable_type: typing_extensions.Literal[cfngin, runway] = 'cfngin') runway.variables.VariableValue
Parse complex variable structures using type appropriate subclasses.
- Parameters
obj – The objected defined as the value of a variable.
variable_type – Type of variable (cfngin|runway).
- pop([index]) item -- remove and return item at index (default last).
Raise IndexError if list is empty or index is out of range.
- remove(value)
S.remove(value) – remove first occurrence of value. Raise ValueError if the value is not present.
- reverse()
S.reverse() – reverse IN PLACE
- class runway.variables.VariableValueLiteral[source]
Bases:
Generic[runway.variables._LiteralValue],runway.variables.VariableValueThe literal value of a variable as provided.
- __init__(value: runway.variables._LiteralValue, variable_type: typing_extensions.Literal[cfngin, runway] = 'cfngin') None[source]
Instantiate class.
- Parameters
value – Data to store in the object.
variable_type – Type of variable (cfngin|runway).
- property resolved: bool
Use to check if the variable value has been resolved.
The ValueLiteral will always appear as resolved because it does not “resolve” since it is the literal definition of the value.
- property value: runway.variables._LiteralValue
Value of the variable.
- __new__(**kwargs)
- property dependencies: Set[Any]
Stack names that this variable depends on.
- classmethod parse_obj(obj: Any, variable_type: typing_extensions.Literal[cfngin, runway] = 'cfngin') runway.variables.VariableValue
Parse complex variable structures using type appropriate subclasses.
- Parameters
obj – The objected defined as the value of a variable.
variable_type – Type of variable (cfngin|runway).
- resolve(context: Union[CfnginContext, RunwayContext], provider: Optional[Provider] = None, variables: Optional[RunwayVariablesDefinition] = None, **kwargs: Any) None
Resolve the variable value.
- Parameters
context – The current context object.
provider – Subclass of the base provider.
variables – Object containing variables passed to Runway.
- property simplified: Any
Return a simplified version of the value.
This can be used to concatenate two literals into one literal or flatten nested concatenations.
Should be implimented in subclasses where applicable.
- class runway.variables.VariableValueConcatenation[source]
Bases:
Generic[runway.variables._VariableValue],runway.variables.VariableValueA concatenated variable values.
- __init__(iterable: Iterable[runway.variables._VariableValue], variable_type: typing_extensions.Literal[cfngin, runway] = 'cfngin') None[source]
Instantiate class.
- Parameters
iterable – Data to store in the iterable.
variable_type – Type of variable (cfngin|runway).
- property simplified: runway.variables.VariableValue
Return a simplified version of the value.
This can be used to concatenate two literals into one literal or flatten nested concatenations.
- property value: Any
Value of the variable. Can be resolved or unresolved.
- Raises
- resolve(context: Union[CfnginContext, RunwayContext], provider: Optional[Provider] = None, variables: Optional[RunwayVariablesDefinition] = None, **kwargs: Any) None[source]
Resolve the variable value.
- Parameters
context – The current context object.
provider – Subclass of the base provider.
variables – Object containing variables passed to Runway.
- __getitem__(__index: int) runway.variables._VariableValue[source]
- __getitem__(__index: slice) List[runway.variables._VariableValue]
Get item by index.
- __setitem__(__index: int, __value: runway.variables._VariableValue) None[source]
- __setitem__(__index: slice, __value: List[runway.variables._VariableValue]) None
Set item by index.
- __new__(**kwargs)
- classmethod parse_obj(obj: Any, variable_type: typing_extensions.Literal[cfngin, runway] = 'cfngin') runway.variables.VariableValue
Parse complex variable structures using type appropriate subclasses.
- Parameters
obj – The objected defined as the value of a variable.
variable_type – Type of variable (cfngin|runway).
- class runway.variables.VariableValueLookup[source]
Bases:
runway.variables.VariableValueA lookup variable value.
- __init__(lookup_name: runway.variables.VariableValueLiteral[str], lookup_query: Union[str, runway.variables.VariableValue], handler: Optional[Type[runway.lookups.handlers.base.LookupHandler]] = None, variable_type: typing_extensions.Literal[cfngin, runway] = 'cfngin') None[source]
Initialize class.
- Parameters
lookup_name – Name of the invoked lookup.
lookup_query – Data portion of the lookup.
handler – Lookup handler that will be use to resolve the value.
variable_type – Type of variable (cfngin|runway).
- Raises
UnknownLookupType – Invalid lookup type.
ValueError – Invalid value for variable_type.
- property simplified: runway.variables.VariableValueLookup
Return a simplified version of the value.
This can be used to concatenate two literals into one literal or flatten nested concatenations.
- property value: Any
Value of the variable. Can be resolved or unresolved.
- Raises
UnresolvedVariableValue – Value accessed before it has been resolved.
- resolve(context: Union[CfnginContext, RunwayContext], provider: Optional[Provider] = None, variables: Optional[RunwayVariablesDefinition] = None, **kwargs: Any) None[source]
Resolve the variable value.
- Parameters
context – The current context object.
provider – Subclass of the base provider.
variables – Object containing variables passed to Runway.
- Raises
FailedLookup – A lookup failed for any reason.
- __iter__() Iterator[runway.variables.VariableValueLookup][source]
How the object is iterated.
- __new__(**kwargs)
- classmethod parse_obj(obj: Any, variable_type: typing_extensions.Literal[cfngin, runway] = 'cfngin') runway.variables.VariableValue
Parse complex variable structures using type appropriate subclasses.
- Parameters
obj – The objected defined as the value of a variable.
variable_type – Type of variable (cfngin|runway).
- class runway.variables.VariableValuePydanticModel[source]
Bases:
Generic[runway.variables._PydanticModelTypeVar],runway.variables.VariableValueA pydantic model variable value.
- __new__(**kwargs)
- classmethod parse_obj(obj: Any, variable_type: typing_extensions.Literal[cfngin, runway] = 'cfngin') runway.variables.VariableValue
Parse complex variable structures using type appropriate subclasses.
- Parameters
obj – The objected defined as the value of a variable.
variable_type – Type of variable (cfngin|runway).
- __init__(data: runway.variables._PydanticModelTypeVar, variable_type: typing_extensions.Literal[cfngin, runway] = 'cfngin') None[source]
Instantiate class.
- Parameters
data – Data to be stored in the object.
variable_type – Type of variable (cfngin|runway).
- property simplified: Dict[str, Any]
Return a simplified version of the value.
This can be used to concatenate two literals into one literal or flatten nested concatenations.
- property value: runway.variables._PydanticModelTypeVar
Value of the variable. Can be resolved or unresolved.
Uses the original pydantic model class to parse the resolved data back into a pydantic model.
- resolve(context: Union[CfnginContext, RunwayContext], provider: Optional[Provider] = None, variables: Optional[RunwayVariablesDefinition] = None, **kwargs: Any) None[source]
Resolve the variable value.
- Parameters
context – The current context object.
provider – Subclass of the base provider.
variables – Object containing variables passed to Runway.
- __getitem__(_VariableValuePydanticModel__key: str) runway.variables.VariableValue[source]
Get item by index.
- __setitem__(_VariableValuePydanticModel__key: str, _VariableValuePydanticModel__value: runway.variables.VariableValue) None[source]
Set item by index.
Advanced Configuration
This section has been placed in the Developer Guide because it details advanced configuration that should only be used by those with intimate knowledge of how Runway works.
Environment Variables
Environment variables can be used to alter the functionality of Runway.
- CI: Any
If not undefined, Runway will operate in non-iterative mode.
- DEBUG: int = 0
Used to select the debug logs to display
0or not defined with show no debug logs1will show Runway’s debug logs2will show Runway’s debug logs and some dependency debug logs (e.g. botocore)
New in version 1.10.0.
- DEPLOY_ENVIRONMENT: str
Explicitly define the deploy environment.
New in version 1.3.4.
- CFNGIN_STACK_POLL_TIME: int = 30
Number of seconds between CloudFormation API calls. Adjusting this will impact API throttling.
- RUNWAY_COLORIZE: str
Explicitly enable/disable colorized output for CDK, Serverless, and Terraform modules. Having this set to a truthy value will prevent
-no-color/--no-colorfrom being added to any commands even if stdout is not a TTY. Having this set to a falsy value will include-no-color/--no-colorin commands even if stdout is a TTY. If the IaC tool has other mechanisms for disabling color output, using a truthy value will not circumvent them.Truthy values are
y,yes,t,true,onand1. Falsy values aren,no,f,false,offand0. RaisesValueErrorif anything else is used.New in version 1.8.1.
- RUNWAY_MAX_CONCURRENT_MODULES: int
Max number of modules that can be deployed to concurrently. (default:
min(61, os.cpu_count()))On Windows, this must be equal to or lower than
61.IMPORTANT: When using
parallel_regionsandchild_modulestogether, please consider the nature of their relationship when manually setting this value. (parallel_regions * child_modules)New in version 1.4.3.
- RUNWAY_MAX_CONCURRENT_REGIONS: int
Max number of regions that can be deployed to concurrently. (default:
min(61, os.cpu_count()))On Windows, this must be equal to or lower than
61.IMPORTANT: When using
parallel_regionsandchild_modulestogether, please consider the nature of their relationship when manually setting this value. (parallel_regions * child_modules)New in version 1.4.3.
- RUNWAY_LOG_FIELD_STYLES: str
Can be provided to customize the styling (color, bold, etc) used for LogRecord attributes (except for message). By default, Runway does not apply style to fields. For information on how to format the value, see the documentation provided by coloredlogs.
New in version 1.10.0.
- RUNWAY_LOG_FORMAT: str
Can be provided to use a custom log message format. The value should be a format string using %-formatting. In addition to being able to use LogRecord attributes in the string, Runway provides the additional fields of
%(hostname)sand%(programname)s.If not provided,
[%(programname)s] %(message)sis used unless using debug, verbose or no color. In that case,%(levelname)s:%(name)s:%(message)sis used.New in version 1.10.0.
- RUNWAY_LOG_LEVEL_STYLES: str
Can be provided to customize the styling (color, bold, etc) used for log messages sent to each log level. If provided, the parsed value will be merged with Runway’s default styling. For information on how to format the value, see the documentation provided by coloredlogs.
New in version 1.10.0.
- RUNWAY_NO_COLOR: Any
Disable Runway’s colorized logs. Providing this will also change the log format to
%(levelname)s:%(name)s:%(message)s.New in version 1.8.1.
- VERBOSE: Any
If not undefined, Runway will display verbose logs and change the logging format to
%(levelname)s:%(name)s:%(message)s.New in version 1.10.0.
Contribution Requirements
Please review our Getting Started Guide for Developers before working on your contribution. It contains information on setting up a development environment to make following some of these requirements easier.
Branch Requirements
Branches must start with one of the following prefixes (e.g. <prefix>/<your-branch-name>).
This is due to how labels are applied to PRs.
If the branch does not meet the requirement, any PRs from it will be blocked from being merged.
- bugfix | fix | hotfix
The branch contains a fix for a big.
- feature | feat
The branch contains a new feature or enhancement to an existing feature.
- docs | documentation
The branch only contains updates to documentation.
- maintain | maint | maintenance
The branch does not contain changes to the project itself to is aimed at maintaining the repo, CI/CD, or testing infrastructure. (e.g. README, GitHub action, integration test infrastructure)
- release
Reserved for maintainers to prepare for the release of a new version.
Documentation Requirements
Docstrings
In general, we loosely follow the Google Python Style Guide for Comments and Docstrings.
We use the napoleon extension for Sphinx to parse docstrings.
Napoleon provides an Example Google Style Python Docstring that can be referenced.
reStructuredText Formatting
In general, we loosely follow the Python Style Guide for documentation.
Note
Not all documentation pages follow this yet. If the page you are updating deviates from this format, adapt to the format of the page.
Section headers are created by underlining (and optionally overlining) the section title with a punctuation character, at least as long as the text.
#with overline, for h1 (generally only one per file, at the top of the file)*with overline, for h2=, for h3-, for h4^, for h5", for h6
h1 and h2 should have two blank lines separating them from sections with headings of the same level or higher.
A ‘’rubric’’ directive can be used to create a non-indexed heading.
Example
#########
Heading 1
#########
*********
Heading 2
*********
Heading 3
=========
Heading 4
---------
Heading 5
^^^^^^^^^
Heading 6
"""""""""
.. rubric:: Non-indexed Heading
*********
Heading 2
*********
Heading 3
=========
PR Requirements
In order for a PR to be merged it must be passing all checks and be approved by at least one maintainer.
Some of the checks can be run locally using make lint and make test.
To be considered for approval, the PR must meet the following requirements.
PR title must be a brief explanation of what was done in the PR (think commit message).
PR body must comply with the formatting and prompts provided in the template (automatically applied when creating a PR on GitHub). At a minimum the following should be provided in the body of the PR:
A summary of was done.
Explain why this change is needed.
Detail the changes that were made (think CHANGELOG).
Include tests for any new features or changes to existing features. (unit tests and integration tests depending on the nature of the change)
Documentation was updated for any new feature or changes to existing features.
Custom Plugin Support
Need to expand Runway to wrap other tools? Yes - you can do that with custom plugin support.
Overview
Runway can import Python modules that can perform custom deployments with your own set of Runway modules. Let’s say for example you want to have Runway execute an Ansible playbook to create an EC2 security group as one of the steps in the middle of your Runway deployment list - this is possible with your own plugin. The custom plugin support allows you to mix-and-match natively supported modules (e.g. CloudFormation, Terraform) with plugins you write providing additional support for non-native modules. Although written in Python, these plugins can natively execute non-Python binaries.
RunwayModule Class
Runway provides RunwayModule to use as the base class of all module handler classes.
This base class will give you the ability to write your own module handler class that can be added to your runway.yml deployment list (More info on runway.yml below).
There are four methods that need to be defined for the class:
- deploy
This method is called when
runway deployis run.- destroy
This method is called when
runway destroyis run.- init
This method is called when
runway initis run.- plan
This method is called when
runway planis run.
Context Object
self.ctx includes many helpful resources for use in your Python module.
Some notable examples are:
self.ctx.env.name- name of the environmentself.ctx.env.aws_region- region in which the module is being executedself.ctx.env.vars- OS environment variables provided to the moduleself.path- path to your Runway module folder
runway.yml Example
After you have written your plugin, you need to add the module class_path
to your module’s configuration. Below is an example runway.yml containing a
single module that looks for an Ansible playbook in a folder at the root of
your Runway environment (i.e. repo) named “security_group.ansible”.
Setting class_path tells Runway to import the DeployToAWS Python class,
from a file named Ansible.py in a folder named “local_runway_extensions”
(Standard Python import conventions apply). Runway will execute the deploy
function in your class when you perform a runway deploy (AKA takeoff).
deployments:
- modules:
- path: security_group.ansible
class_path: local_runway_extensions.Ansible.DeployToAWS
regions:
- us-east-1
Below is the Ansible.py module referenced above that wraps the
ansible-playbook command. It will be responsible for deploying an EC2 Security Group from the playbook
with a naming convention of <env>-<region>.yaml within a fictional
security_group.ansible Runway module folder. In this example, the
ansible-playbook binary would already have been installed prior to a Runway
deploy, but this example does check to see if it is installed before execution
and logs an error if not. The Runway plugin will only execute
the ansible-playbook against a yaml file associated with the environment and set for the Runway
execution and region defined in the runway.yml.
Using the above runway.yml and the plugin/playbook below saved to the Runway
module folder you will only have a deployment occur in the dev environment
in us-east-1. If you decide to perform a runway deployment in the prod
environment, or in a different region, the ansible-playbook deployment will be
skipped. This matches the behavior of the Runway’s native modules.
"""Ansible Plugin example for Runway."""
from __future__ import annotations
import logging
import subprocess
import sys
from typing import TYPE_CHECKING, Dict
from runway.module.base import RunwayModule
from runway.utils import which
if TYPE_CHECKING:
from pathlib import Path
LOGGER = logging.getLogger("runway")
def check_for_playbook(playbook_path: Path) -> Dict[str, bool]:
"""Determine if environment/region playbook exists."""
if playbook_path.is_file():
LOGGER.info("Processing playbook: %s", playbook_path)
return {"skipped_configs": False}
LOGGER.error(
"No playbook for this environment/region found -- looking for %s",
playbook_path,
)
return {"skipped_configs": True}
class DeployToAWS(RunwayModule):
"""Ansible Runway Module."""
def deploy(self) -> None:
"""Run ansible-playbook."""
if not which("ansible-playbook"):
LOGGER.error(
'"ansible-playbook" not found in path or is not '
"executable; please ensure it is installed"
"correctly."
)
sys.exit(1)
playbook_path = self.path / f"{self.ctx.env.name}-{self.ctx.env.aws_region}"
response = check_for_playbook(playbook_path)
if response["skipped_configs"]:
return
subprocess.check_output(["ansible-playbook", str(playbook_path)])
def destroy(self) -> None:
"""Skip destroy."""
LOGGER.info("destroy not currently supported for Ansible")
def init(self) -> None:
"""Skip init."""
LOGGER.info("init not currently supported for Ansible")
def plan(self) -> None:
"""Skip plan."""
LOGGER.info("plan not currently supported for Ansible")
And below is the example Ansible playbook itself, saved as dev-us-east-1.yaml in the security_group.ansible folder:
- hosts: localhost
connection: local
gather_facts: false
tasks:
- name: create a security group in us-east-1
ec2_group:
name: dmz
description: Dev example ec2 group
region: us-east-1
rules:
- proto: tcp
from_port: 80
to_port: 80
cidr_ip: 0.0.0.0/0
register: security_group
The above would be deployed if runway deploy was executed in the dev environment to us-east-1.
Getting Started
Before getting started, fork this repo and clone your fork.
Development Environment
This project includes an optional VSCode Dev Container. This is an Ubuntu 22.04 image that will launch with operating system pre-requisites already installed and VSCode configured for Python debugging. It’s not required to use this for development work, but does provide an easy and consistent way to get started.
This project uses poetry to create Python virtual environment. This must be installed on your system before setting up your dev environment.
With poetry installed, run make setup to setup your development environment.
This will create all the required virtual environments to work on Runway, build docs locally, and run integration tests locally.
The virtual environments all have Runway installed as editable meaning as you make changes to the code of your local clone, it will be reflected in all the virtual environments.
pre-commit
pre-commit is configured for this project to help developers follow the coding style.
If you used make setup to setup your environment, it is already setup for you.
If not, you can run make setup-pre-commit to to install the pre-commit hooks.
You can also run make run-pre-commit at any time to manually trigger these hooks.
pyright Type Checking
This project uses pyright to perform type checking. To run type checking locally, install pyright (make npm-ci) then run make lint or make lint-pyright.
Building Pyinstaller Packages Locally
We use Pyinstaller to build executables that do not require Python to be installed on a system. These are built by Travis CI for distribution to ensure a consistent environment but they can also be build locally for testing.
Prerequisites
These need to be installed globally.
Process
Export
OS_NAMEenvironment variable for your system (ubuntu-22.04,macos-12, orwindows-latest).Execute
make build-pyinstaller-fileormake build-pyinstaller-folderfrom the root of the repo.
The output of these commands can be found in ./artifacts
Infrastructure
The Runway repository uses some external infrastructure to run tests and server public content.
The code that deploys this infrastructure is located in the infrastructure/ directory.
Each subdirectory is a logical separation between AWS accounts.
Deploying Infrastructure
Infrastructure can be deployed from the root of the infrastructure/ directory for any environment.
We make use of make to simplify the process.
To execute Runway for an environment, use the following command syntax.
$ make <runway-subcommand> <environment>
Example
$ make deploy public
public
AWS account for public facing assets.
Onica SSO Name
onica-public-prod
Resources
public S3 bucket that houses build artifacts
binary executables
IAM user used by GitHub Actions & it’s policies
able to sync with the artifact bucket
add entries to a DynamoDB table for the
oni.caURL shortener apppath to download the binary executables from S3
test
AWS account for running Runway functional tests.
Onica SSO Name
onica-platform-runway-testing-lab
Resources
TBA
test-alt
AWS account for running Runway functional tests that require cross-account access to complete.
Onica SSO Name
onica-platform-runway-testing-alt-lab
Resources
TBA
Release Process
Steps that should be taken when preparing for and executing a release.
Contents
Preparation
Merge all PRs that should be included in the release.
Ensure that all checks have completed and passed on the master branch.
Execution
Navigate to the Releases section of the repository on GitHub. There should be a Draft already started that was automatically generated from PRs that were merged since the last release.
Enter the Edit screen of the Draft.
The Title and Tag fields should already be filled in with the correct values (e.g.
v<major>.<minor>.<patch>). Ensure these values match what is expected. The Tag should also be targeting the master branch.Edit the description of the release as needed but, there should be little to no changes required if all PRs were properly labeled.
Mark the release as a pre-release if applicable (alpha, beta, release candidate, etc).
Publish the release.
At this point, GitHub Actions will begin building the deployment packages & automatically publishing them to npm, PyPi, and AWS S3. The Publish Release workflow can be monitored for progress. It can take around 20 minutes for the process to complete. At which time, the logs and package repositories should be checked to verify that the release was published successfully.
Secrets
Information about the secrets used by this project.
GitHub
GitHub secrets are set in the settings of the repository for use by GitHub Actions.
Environment Secrets
Secrets specific to the repository, specific to a single environment.
- DEPLOY_AWS_ACCESS_KEY_ID
AWS Access Key for the IAM user used to deploy infrastructure to accounts. This is not the user used when running tests but for deploying infrastructure used by tests (including the IAM user running the tests).
- DEPLOY_AWS_SECRET_ACCESS_KEY
AWS Secret Access Key for the IAM user used to deploy infrastructure to accounts. This is not the user used when running tests but for deploying infrastructure used by tests (including the IAM user running the tests).
Repository Secrets
Secrets specific to the repository, available to all environments.
- AWS_ACCESS_KEY
AWS Access Key for the IAM user used to publish artifacts to S3. This IAM user exists in the public AWS account.
- AWS_SECRET_KEY
AWS Secret Access Key for the IAM user used to publish artifacts to S3. This IAM user exists in the public AWS account.
- NPM_API_TOKEN
API access token used to publish Runway to NPM.
- PYPI_PASSWORD
API token used to publish Runway to PyPi. This should be scoped to only the Runway project.
- TEST_PYPI_PASSWORD
Similar to
PYPI_PASSWORDbut for https://test.pypi.org/.
- TEST_RUNNER_AWS_ACCESS_KEY_ID
AWS Access Key for the IAM user used to run tests.
- TEST_RUNNER_AWS_SECRET_ACCESS_KEY
AWS Secret Access Key for the IAM user used to run tests.
ReadTheDocs
Secrets are set as environment variables for ReadTheDocs to use when building documentation.
- SPHINX_GITHUB_CHANGELOG_TOKEN
Used by sphinx-github-changelog to generate a changelog for GitHub Releases. The GitHub personal access token scope only needs to include
repo.public_repo.
CHANGELOG
Apache License
- Version
2.0
- Date
January 2004
- URL
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APPENDIX: How to apply the Apache License to your work
To apply the Apache License to your work, attach the following boilerplate notice, with the fields enclosed by brackets “[]” replaced with your own identifying information. (Don’t include the brackets!) The text should be enclosed in the appropriate comment syntax for the file format. We also recommend that a file or class name and description of purpose be included on the same “printed page” as the copyright notice for easier identification within third-party archives.
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Terminology
Runway
Deploy Environment
Deploy environments are used for selecting the options/variables/parameters to be used with each Module.
The deploy environment is derived from the current directory (if its not a git repo), active git branch, or environment variable (DEPLOY_ENVIRONMENT).
Standard deploy environments would be something like prod, dev, and test.
When using a git branch, Runway expects the branch to be prefixed with ENV-. If this is found, Runway knows that it should always use the value that follows the prefix. If it’s the master branch, Runway will use the deploy environment name of common. If the branch name does not follow either of these schemas and Runway is being run interactively from the CLI, it will prompt of confirmation of the deploy environment that should be used.
When using a directory, Runway expects the directory’s name to be prefixed with ENV-. If this is found, Runway knows that it should always use the value that follows the prefix.
Deployment
A deployment contains a list of modules and options for all the modules in the deployment. A Runway Config File can contain multiple deployments and a deployment can contain multiple modules.
Lookup (Runway)
A method for expanding values in the Runway Config File file when processing a deployment/module. These are only supported in select areas of the Runway Config File (see the config docs for more details).
Module
A module is a directory containing a single infrastructure-as-code tool configuration of an application, a component, or some infrastructure (eg. a set of CloudFormation templates).
It is defined in a deployment by path.
Modules can also contain granular options that only pertain to it based on its module.type.
Parameters
A mapping of key: value that is passed to a module.
Through the use of a Lookup (Runway), the value can be changed per region or deploy environment.
The value can be any data type but, support for complex data types depends on the module.type.
Runway’s CFngin
Blueprint
A python class that is responsible for creating a CloudFormation template. Usually this is built using troposphere.
context
Context is responsible for translating the values passed in via the
command line and specified in the config to stacks.
graph
A mapping of object name to set/list of dependencies.
A graph is constructed for each execution of CFNgin from the contents of the
config file.
Example
{
"stack1": [],
"stack2": [
"stack1"
]
}
stack1 depends on nothing.
stack2 depends on stack1
lookup
A method for expanding values in the config at runtime. By default
lookups are used to reference Output values from other stacks within the
same namespace.
output
A CloudFormation Template concept.
Stacks can output values, allowing easy access to those values.
Often used to export the unique ID’s of resources that templates create.
CFNgin makes it simple to pull outputs from one stack and then use them in the variables of another stack.